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Centralized access control systems are unsuitable for IoT due to their resource-constrained, heterogeneous, and dynamic nature. Blockchain-assisted decentralized access control systems exist for IoT, but those approaches are tokenization-based. In some cases, IoT devices are not part of the blockchain network due to which they cannot interact with the access control system directly. Instead, they need a trusted admin, management hub, or a fog node for permissions verification and access to resources. This paper presents a smart contract and blockchain-assisted framework for the access control systems in the IoT enterprise environment, called ACS-IoT. In the proposed framework, resource-constrained IoT devices belong to the blockchain network. Therefore, these devices can directly access the permitted resources without any centrally administered authority and management hub's verification. We used smart contract and Ethereum blockchain for the new framework. Smart contract allows automated enforcement of access policies and serves as an autonomous agent running exactly as programmed. The proposed framework is validated through implementation of the proof of concept, and implemented prototype is deployed and tested on the Ethereum test network. The obtained results confirm that usage of blockchain and smart contract can be used as access management technology in the IoT enterprise environment. [ABSTRACT FROM AUTHOR]

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Data security on the Internet of Things (IoT) is usually implemented through encryption. This paper presents a solution based on routing, in which data are forwarded only to entities that are intended to receive them according to security requirements of secrecy (also called confidentiality), integrity, and conflicts. Our solution is generic in the sense that it can be used in any network, together with encryption as appropriate. We use the fact that, in any network, security requirements generate a partial order of equivalence classes of entities, and each entity can be labeled according to the position of its equivalence class in the partial order. Routing tables among entities can be compiled using the labels. The method is demonstrated in this paper for software-defined networking (SDN) routers and controllers. We propose a centralized IoT architecture with a cloud structure using SDN as networking infrastructure, where storage entities (i.e., cloud servers) are associated with application entities. A small 'hospital' example is shown for illustration. Procedures for network reconfigurations are presented. We also demonstrate the method for the normal case where different partial orders, representing distinct but concurrent security requirements, coexist among a set of entities. The method proposed does not impose an overhead on the normal functioning of SDN networks since it requires calculations only when the network must be reconfigured because of administrative intervention or policies. These occasional updates can be done efficiently and offline. [ABSTRACT FROM AUTHOR]

The blockchain-based Electronic Medical Record (EMR) data storage system encounters challenges which are data leakage, insufficient access control, and low retrieval efficiency. In response to these issues, this paper proposes a lightweight searchable encryption and access control system for sharing EMR data securely. The lightweight searchable encryption scheme which is achieved by integrating the trapdoor verification phase with the keyword retrieval phase is constructed using BGG13 + and MP12. User access control is implemented through a Boolean circuit to replace arithmetic operations and thus improve arithmetic efficiency. Since logic operations can reduce the computation time, this paper uses Boolean circuits for user rights verification implementation. In addition, this paper adopts the Bloom filter as the system index to enhance the efficiency of block-chain data retrieval. According to the simulation results, there is a performance advantage of this system over similar systems. [ABSTRACT FROM AUTHOR]

In recent years, with the increasing number of terminal connections, high-density deployment scenarios have become important scenarios for future wireless networks. Ultra-high throughput (EHT) in high density deployment scenarios is the technical goal of IEEE 802.11be, the next-generation wireless local area network (WLAN) standard. However, in a high-density deployment scenario, interference suppression between BSSs is serious, which seriously affects the throughput of a WLAN. And the resources available are limited. Therefore, for the next generation WLAN standard, this paper proposes a downlink transmission scheme based on AP coordination and the orthogonal frequency division multiple access (OFDMA) protocol and the non-orthogonal multiple access (NOMA) protocol, named Co-OFDMA–NOMA scheme. The core idea is to transform the interference and suppression relationship between neighboring BSSs into the relationship of mutual coordination and assistance through the Co-OFDMA–NOMA protocol proposed in this paper. Firstly, a downlink transmission scheme named the Co-OFDMA–NOMA protocol is designed. In addition, the protocol and its framework structure have good backward compatibility. Theoretical analysis shows that the proposed Co-OFDMA–NOMA protocol has significant performance gain, and simulation results prove the effectiveness of the scheme. [ABSTRACT FROM AUTHOR]

Cloud computing has transformed the way businesses and individuals manage, store, and process data, offering scalable, on-demand resources that drive innovation and efficiency. However, the adoption of cloud services also introduces significant cybersecurity challenges, particularly in the areas of data protection and privacy. This paper provides a comprehensive analysis of the vulnerabilities inherent in cloud environments and explores various advanced techniques for safeguarding data and ensuring privacy. Key areas of focus include encryption (for data at rest, in transit, and in use), access control and identity management, data masking, anonymization, secure multi-party computation, homomorphic encryption, and zero-knowledge proofs. The paper further examines secure cloud architecture frameworks, emphasizing the role of security-by-design principles, segmentation, isolation, and the use of security zones to enhance overall system security. A comparative analysis evaluates the effectiveness of different security measures based on criteria such as performance, scalability, and ease of implementation. The discussion also highlights emerging trends and technologies, including AI-driven security solutions and quantum-resistant encryption, as well as the evolving regulatory landscape and its impact on cloud security strategies. The findings underscore the critical importance of a multi-layered security approach in mitigating risks and protecting sensitive data in cloud environments. The paper concludes with recommendations for future research and development to address ongoing and emerging challenges in cloud cybersecurity, emphasizing the need for continuous innovation to keep pace with the evolving threat landscape. [ABSTRACT FROM AUTHOR]

Electronic medical records have the advantages of large storage capacity, convenience, improved efficiency, etc. However, since electronic medical records contain a large amount of patient's private information, if they are stored directly in the cloud server, patients may face the risk of privacy data leakage and electronic medical record data tampering. To solve the above problems, this paper proposes a secure sharing scheme of electronic medical records combining quantum key and blockchain. Based on the true randomness of quantum keys, the multi-user secure forwarding mechanism of quantum keys is designed using proxy re-encryption technology and blockchain. A fine-grained access control scheme for electronic medical records by users with different roles was proposed using data desensitization technology. To facilitate secure retrieval from the cloud server, searchable encryption technology is used. This paper analyzes the comprehensive performance level of the proposed scheme through blockchain performance testing and system efficiency testing. [ABSTRACT FROM AUTHOR]

In specific private cloud scenarios, how to defend against malicious software and ensure data security is one of the current research hotspots, and sandbox is an important detection method. This paper proposes a dynamic behavior detection technique based on sandboxing, which real-time monitors and analyzes malicious software behavior. By improving the sandbox behavior weight, integrating virtual resources, and designing fine-grained access control, the detection accuracy and efficiency are enhanced based on zero trust access control system. The simulated attacks are identified on the testing platform, drawing knowledge graphs, achieving effective discovery and tracing. Meanwhile, this paper verified through experiments that the system consumption of the detection method is within an acceptable range, expanding the detection range and reducing the missed detection rate. [ABSTRACT FROM AUTHOR]

With the rapid advancement of cloud computing technology, reversible data hiding algorithms in encrypted images (RDH-EI) have developed into an important field of study concentrated on safeguarding privacy in distributed cloud environments. However, existing algorithms often suffer from low embedding capacities and are inadequate for complex data access scenarios. To address these challenges, this paper proposes a novel reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and ciphertext-policy attribute-based encryption (CP-ABE). This proposed algorithm enhances the conventional median edge detection (MED) by incorporating dynamic variables to improve pixel prediction accuracy. The carrier image is subsequently reconstructed using the Huffman coding technique. Encrypted image generation is then achieved by encrypting the image based on system user attributes and data access rights, with the hierarchical embedding of the group’s secret data seamlessly integrated during the encryption process using the CP-ABE scheme. Ultimately, the encrypted image is transmitted to the data hider, enabling independent embedding of the secret data and resulting in the creation of the marked encrypted image. This approach allows only the receiver to extract the authorized group’s secret data, thereby enabling fine-grained, controlled access. Test results indicate that, in contrast to current algorithms, the method introduced here considerably improves the embedding rate while preserving lossless image recovery. Specifically, the average maximum embedding rates for the (3, 4)-threshold and (6, 6)-threshold schemes reach 5.7853 bits per pixel (bpp) and 7.7781 bpp, respectively, across the BOSSbase, BOW-2, and USD databases. Furthermore, the algorithm facilitates permission-granting and joint-decryption capabilities. Additionally, this paper conducts a comprehensive examination of the algorithm’s robustness using metrics such as image correlation, information entropy, and number of pixel change rate (NPCR), confirming its high level of security. Overall, the algorithm can be applied in a multi-user and multi-level cloud service environment to realize the secure storage of carrier images and secret data. [ABSTRACT FROM AUTHOR]

Considering human influence and its negative impact on the environment, the world will have to transform the current energy system into a cleaner and more sustainable one. In residential as well as office buildings, there is a demand to minimize electricity consumption, improve the automation of electrical appliances and optimize electricity utilization. This paper describes the implementation of a smart switch with extended facilities compared to traditional switches, such as visual indication of evacuation routes in case of fire and acoustic alerts for emergencies. The proposed embedded system implements Modbus RTU serial communication to receive information from a fire alarm-control panel. An extension to the Modbus communication protocol, called Modbus Extended (ModbusE), is also proposed for smart switches and emergency switchboards. The embedded smart switch described in this paper as a scientific and practical contribution in this field, based on a performant microcontroller system, is integrated into the Building Internet of Things (BIoT) concept and uses the innovative ModbusE protocol. The proposed smart lighting system integrates building lighting access control for smart switches and sockets and can be extended to incorporate functionality for smart thermostats, access control and smart sensor-based information acquisition. [ABSTRACT FROM AUTHOR]

The widespread adoption of cloud computing has dramatically altered how data is stored, processed, and accessed in an era. The rapid development of digital technologies characterizes all this. The widespread adoption of cloud services has introduced new obstacles to guaranteeing secure and expeditious access to sensitive data. Organizations of all types find user-friendly and cost-effective solutions crucial, which is why they consider cloud services essential. The availability of the cloud hampers access control security in systems that are constantly and remotely changing. Conventional methods of access control are efficient, but the advanced world of technology exposes them to more threats. Applying blockchain technology to cloud access control systems, which are decentralized, transparent, and tamper-proof, has overcome these challenges. This paper aims to discuss the potential of blockchain in enhancing access management, security and trust in cloud computing. Besides, this scholarly article reviews the evolving area of blockchain-based access control systems and synthesizes the findings of 118 selected papers from various academic repositories. Based on this systematic review of the studies, twelve different types of blockchain-based access control paradigms can be identified. This work provides a critical analysis of the research on blockchain technology in access control systems, with a focus on scalability, compatibility, and security challenges. It also highlights areas that require further research and proposes directions for future research to advance this rapidly growing area of scholarship. [ABSTRACT FROM AUTHOR]

In response to the challenges of generating Attribute-Based Access Control (ABAC) policies, this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents. This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model. The manual retrieval and analysis involved in this transition are inefficient, prone to errors, and costly. Most organizations have high-level specifications defined for security policies that include a set of access control policies, which often exist in the form of natural language documents. Utilizing this rich source of information, our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents, thereby constructing and optimizing access control policies. This work transforms the problem of policy automation generation into two tasks: extraction of access control statements and mining of access control attributes. First, the Chat General Language Model (ChatGLM) is employed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model's In-Context Learning to contextualize the statements. Then, the Iterated Dilated-Convolutions-Conditional Random Field (ID-CNN-CRF) model is used to annotate access control attributes within these extracted statements, including subject attributes, object attributes, and action attributes, thus reassembling new access control policies. Experimental results show that our method, compared to baseline methods, achieved the highest F1 score of 0.961, confirming the model's effectiveness and accuracy. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is the underlying technology that has enabled connecting daily apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is experiencing an impressive 16.7% growth rate and is a nearly USD 300.3 billion market. These eye-catching figures have made it an attractive playground for cybercriminals. IoT devices are built using resource-constrained architecture to offer compact sizes and competitive prices. As a result, integrating sophisticated cybersecurity features is beyond the scope of the computational capabilities of IoT. All of these have contributed to a surge in IoT intrusion. This paper presents an LSTM-based Intrusion Detection System (IDS) with a Dynamic Access Control (DAC) algorithm that not only detects but also defends against intrusion. This novel approach has achieved an impressive 97.16% validation accuracy. Unlike most of the IDSs, the model of the proposed IDS has been selected and optimized through mathematical analysis. Additionally, it boasts the ability to identify a wider range of threats (14 to be exact) compared to other IDS solutions, translating to enhanced security. Furthermore, it has been fine-tuned to strike a balance between accurately flagging threats and minimizing false alarms. Its impressive performance metrics (precision, recall, and F1 score all hovering around 97%) showcase the potential of this innovative IDS to elevate IoT security. The proposed IDS boasts an impressive detection rate, exceeding 98%. This high accuracy instills confidence in its reliability. Furthermore, its lightning-fast response time, averaging under 1.2 s, positions it among the fastest intrusion detection systems available. [ABSTRACT FROM AUTHOR]

Online health consultations are becoming more popular as a result of technological improvements. Patients routinely look for information about medical disorders online, which could jeopardize the privacy of medical records and increase the workload of healthcare professionals. Nonetheless, academics continue to be extremely concerned about issues related to the quality characteristics that relate to the current architectural models, such as energy consumption, latency, resource utilization, scalability, and packet loss. This method, however, also results in a significant strain being placed on medical experts who must sort through vast amounts of medical records to extract certain information. This paper presents a novel ciphertext policy attribute-based encryption method coupled with fuzzy logic to overcome these issues. This solution uses a hybrid structure of IPFS and blockchain to store data and enables complex bidirectional access control. Before being added to IPFS, medical records are encrypted. To ensure data integrity, related IPFS hash indexes are then added to the blockchain. Utilizing attribute-based technology, users' data is encrypted to give them fine-grained bidirectional access control. A thorough security analysis proves the system's resilience, especially when faced with chosen plaintext assaults inside the random oracle model. Tests for this study were conducted using 10–50 attribute sets. This paper's technique solely makes use of a hash operation. All things considered; the study demonstrates that the proposed design is more efficient than earlier schemes. Thus, from the comparison study above, it can be concluded that the system presented in this work is more efficient. Results from simulations provide additional support for the suggested methodology by highlighting the improved computing efficiency of users as compared to baseline conventional systems. This study demonstrates how technological advancement and healthcare requirements can coexist harmoniously, paving the way for secure and effective online medical consultations that are powered by fuzzy logic. [ABSTRACT FROM AUTHOR]

Ensuring the confidentiality, integrity, and availability of sensitive data in cloud environments relies heavily on the robust management of cryptographic keys. With the expansion of cloud usage and the increase in data volumes, ensuring the security and reliability of key management services is becoming an essential aspect of overall cloud security. These policies encompass various aspects, such as the lifecycle management of keys, controlling access, encryption protocols, and safeguarding keys, all of which collectively contribute to enhanced security and compliance with regulatory requirements. Two case studies demonstrate the application of existing frameworks in a financial institution and a healthcare organization. The paper concludes by highlighting potential applications and use cases across different industries. This study introduces a secure application management framework within the realm of cloud security called the secure policies of cloud security framework (SPCSF). SPCSF is built around the idea of implementing precise control over application permissions and encrypting REST API communications to enhance protection against malicious attacks. The framework is made up of two main parts: (i) a permission detection engine that determines whether an application's permissions are legitimate. By looking at permission manifests, byte codes, and cross-referencing permissions against a well-defined list of sensitive APIs, it accomplishes this. (ii) Registration Authorization Engine: this engine makes it easier for applications to register securely with the controller. It makes use of a suggested technique for safe authentication, allowing or denying applications access to requested REST APIs based on the level of danger they pose. With this strategy, approved and secure access to vital resources is guaranteed. [ABSTRACT FROM AUTHOR]

Wireless communications play an important role in ensuring ease of access to shared electronic health records (EHR) across health service providers which is essential and significant for prompt patients' care, especially in cases of emergency medical conditions. With the need to support anytime, anywhere access to, potentially bandwidth hungry, medical records, electronic healthcare applications will continue to benefit from advanced wireless network technologies such as 5G and beyond. With sharing, it is crucial to provide patients with security and privacy guarantees, and allow them to certain control of access to their data. Existing solutions mostly assume that patients are available to authorize requests to access their EHR, which is impractical as the patient may be unconscious. This paper proposes a secure and privacy protecting protocol whereby the patient can pre-delegate the authorization for the access of his/her EHR. Our patient(user)-centric proposal combines Self-Sovereign Identity (SSI) concepts and model with Secure Multi-party Computation (SMPC) and Threshold Cryptography (TC) to enable secure identity and authorization verification. A block cipher encryption sharing approach is adopted for the threshold SMPC which extends the AES-GCM symmetric encryption model into a full-fledged cryptographic platform. Two mechanisms are implemented for the block cipher encryption, namely XOR and Cascade, and experiments are conducted to compare them. We conclude that the XOR mechanism can scale for larger thresholds, while Cascade performed better for a lower threshold (≤ 3). This paper also performs a threat analysis of the protocol and approach, and validates its correctness and complexity. We conclude that the approach can achieve the security and privacy protection of the patient's personal EHR, as well as the autonomy of the patient to control the authorization for the access and sharing. [ABSTRACT FROM AUTHOR]

Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes. A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy protection. Recent investigations have explored cutting-edge methods, such as leveraging blockchain for transaction recording to enhance security and privacy, along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Moreover, the analysis indicates that encryption and hashing techniques are prevalent in the data plane, whereas access control and certificate authorization are prominently considered in the control plane, and authentication is commonly employed within the application plane. Additionally, this paper outlines future directions, offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem. [ABSTRACT FROM AUTHOR]

To ensure optimal use of images while preserving privacy, it is necessary to partition the shared image into public and private areas, with public areas being openly accessible and private areas being shared in a controlled and privacy-preserving manner. Current works only facilitate image-level sharing and use common cryptographic algorithms. To ensure efficient, controlled, and privacy-preserving image sharing at the area level, this paper proposes an image partition security-sharing mechanism based on blockchain and chaotic encryption, which mainly includes a fine-grained access control method based on Attribute-Based Access Control (ABAC) and an image-specific chaotic encryption scheme. The proposed fine-grained access control method employs smart contracts based on the ABAC model to achieve automatic access control for private areas. It employs a Cuckoo filter-based transaction retrieval technique to enhance the efficiency of smart contracts in retrieving security attributes and policies on the blockchain. The proposed chaotic encryption scheme generates keys based on the private areas' security attributes, largely reducing the number of keys required. It also provides efficient encryption with vector operation acceleration. The security analysis and performance evaluation were conducted comprehensively. The results show that the proposed mechanism has lower time overhead than current works as the number of images increases. [ABSTRACT FROM AUTHOR]

Location-based services (LBS) offer various functionalities, but ensuring secure access to sensitive user data remains a challenge. Traditional access control methods often need more detail to enforce location-specific restrictions. This paper proposes a new approach that utilizes the Generalized Spatio-Temporal Role-Based Access Control Model (GSTRBAC) within the context of LBS. GSTRBAC grants access based on user credentials, authorized locations, and access times, providing a detailed approach to securing LBS data. We introduce an optimized cloud-based GSTRBAC implementation suitable for deployment in modern LBS architectures. The system uses two secure communication protocols tailored to different security requirements. This allows for efficient communication for less-sensitive data while offering robust protection for highly sensitive information. Additionally, a proof-of-concept mobile application demonstrates the system's functionality and efficiency within an LBS environment. Our evaluation confirms the effectiveness of the cloud-based GSTRBAC implementation in enforcing location-specific access control while maintaining resource and time efficiency. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has recently received a great deal of research interest due to its broad range of applications. One of the important layers in IoT applications is known as edge computing where resource-constrained devices at the edge form a simple type of network to sense required data. A more powerful edge device is responsible for collecting all sensed data to be transferred to the upper layers. A critical focus is therefore placed on maximum rate of data collection, requiring effective and intelligent solutions to coordinate the channel access of the devices. Medium access control (MAC) protocols take this responsibility as their design mission. Carrier-sense multiple access (CSMA) has been a baseline MAC scheme and many previous traditional networks utilized a CSMA-based solution. The motivation of this paper is to study the performance of a typical network at the edge through the CSMA theme. A practical network is constructed to assess the channel throughput performance via a commercially available radio transceiver. The practical performance observations indicate the suitability of the proposed CSMA-based solution. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks are self-organizing networks that do not rely on fixed infrastructure. Smart antennas employ advanced beamforming technology, enabling ultra-long-range directional transmission in wireless networks, which leads to lower power consumption and better utilization of spatial resources. The media access control (MAC) protocol design using smart antennas can lead to efficient usage of channel resources. However, during ultra-long-distance transmissions, there may be significant transport delays. In addition, when using the time division multiple access (TDMA) schemes, it can be difficult to manage conflicts arising from adjacent time slot advancement caused by latency compensation in ultra-long-range propagation. Directional transmission and reception can also cause interference between links that reuse the same time slot. This paper proposes a new distributed dynamic TDMA protocol called State Interaction-based Slot Allocation Protocol (SISAP) to address these issues. This protocol is based on slot states and includes TDMA frame structure, slot allocation process, interference self-avoidance strategy, and slot allocation algorithms. According to the simulation results, the MAC layer design scheme suggested in this paper can achieve ultra-long-distance transmission without conflicts. Additionally, it can reduce the interference between links while space multiplexing. Furthermore, the system exhibits remarkable performance in various network aspects, such as throughput and link delay. [ABSTRACT FROM AUTHOR]

The emergence of Internet of Things (IoT) technology brings tremendous benefits to people's lives and work. However, the integration of IoT devices into diverse systems has underscored the pressing issue of security. Safeguarding data confidentiality in IoT systems necessitates the implementation of strong security measures, including authentication, encryption and access control mechanisms. When effectively employed, these measures pave the way for the development of an efficient and secure IoT system, offering substantial benefits to end-users. This paper introduces a novel authentication and access control solution tailored for IoT edge devices. Our suggested approach is applicable to the edge network comprising numerous nodes, enabling the transmission of extensive data within constrained bandwidth based on lightweight symmetric cryptography since it uses Chacha20 algorithm to establishing session key, and maintaining the protocol of identity management and access control more precisely through HoBAC and blockchain technology. We have successfully analyzed the protocol correctness using the scyther tool. The results demonstrate the superiority of the proposed protocol compared to alternative approaches, particularly in terms of communication and time costs. [ABSTRACT FROM AUTHOR]

As network technology advances and more people use devices, data storage has become a significant challenge due to the explosive growth of information and the threat of data leaks. In traditional medical institutions, most medical data is stored centrally through cloud computing technology in the institution's data center. This centralized storage method has many security risks, and once the central server is attacked, it will lead to the loss of medical data, which will lead to the leakage of patients' private data. At the same time, electronic medical records are the most critical data in the current medical field. In the traditional centralized healthcare service system (HSS), there are data leakage problems and tampering with electronic medical records due to human factors. At the same time, each hospital is built independently, resulting in the current centralized healthcare service system having a data silo problem, making it difficult to share medical data between institutions securely. With the increase in the number of users in the system, the electronic medical record data in the system also increases gradually, resulting in the increasing overhead of decryption calculation. Therefore, this paper proposes a blockchain-based access control scheme with multiparty authorization to ensure the security of electronic medical records. The scheme uses an SM encryption algorithm to encrypt the medical data in the system. It adds the patient's signature to ensure the confidentiality and security of the data, and the encrypted electronic medical records (EMRs) are stored in the InterPlanetary File System (IPFS) to realize the distributed storage of EMR. In addition, role-based multiauthorization access control is implemented through smart contract-based to ensure the security of EMR. We have analyzed the security of this paper's solution and compared its performance with the existing schemes based on other cryptographic algorithms. The experimental results show that the proposed solution significantly improves the secure sharing of EMR and provides system performance. [ABSTRACT FROM AUTHOR]

The centralized storage and centralized authorization approach in medical information systems can lead to data tampering and private information privacy leakage, while the traditional access control model has an overly simple authentication approach, relies excessively on trusted third-party organizations for the enforcement of access control policies, and has low efficiency in processing access requests. To address these problems, this paper proposes an access control model based on the collaboration of blockchain main and side chains, AC-BMS. Firstly, a password-based authentication scheme is designed based on doctors' identity information; then Polygon side chain is designed to enhance the storage scalability of the blockchain; finally, the access node information on the main Ethereum chain is located on the side chain, and resources are obtained by executing Roll-up contracts deployed on the side chain. It is confirmed by simulation experiments in Hyperledger Fabric that the access efficiency and throughput of the blockchain access model proposed in this paper are improved when the number of accesses is multiplied, the average access time is saved by 2–3 s, the latency time is floating and stable, and the security, scalability, and availability are enhanced. [ABSTRACT FROM AUTHOR]

Purpose: Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today's sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art. Design/methodology/approach: This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements. Findings: As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements. Originality/value: This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today's sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models. [ABSTRACT FROM AUTHOR]

With the application of robotics in security monitoring, medical care, image analysis, and other high-privacy fields, vision sensor data in robotic operating systems (ROS) faces the challenge of enhancing secure storage and transmission. Recently, it has been proposed that the distributed advantages of blockchain be taken advantage of to improve the security of data in ROS. Still, it has limitations such as high latency and large resource consumption. To address these issues, this paper introduces PrivShieldROS, an extended robotic operating system developed by InterPlanetary File System (IPFS), blockchain, and HybridABEnc to enhance the confidentiality and security of vision sensor data in ROS. The system takes advantage of the decentralized nature of IPFS to enhance data availability and robustness while combining HybridABEnc for fine-grained access control. In addition, it ensures the security and confidentiality of the data distribution mechanism by using blockchain technology to store data content identifiers (CID) persistently. Finally, the effectiveness of this system is verified by three experiments. Compared with the state-of-the-art blockchain-extended ROS, PrivShieldROS shows improvements in key metrics. This paper has been partly submitted to IROS 2024. [ABSTRACT FROM AUTHOR]

As mobile communications transform, 5G technology can potentially change many industries and businesses. The change will have a great influence across many fields, such as the automotive, healthcare, and manufacturing sectors. This paper aims to review the existing applications of blockchain technology in providing 5G network security and identify new possibilities for such security solutions. We consider different aspects of blockchain in 5G, particularly data transmission, access control, and applications including vertical industry-oriented applications and specific solutions supporting such sectors of economic activity. The paper briefly describes modern technologies in 5G networks and introduces blockchain's properties and different aspects of using such technology in practical applications. It also presents access control management with blockchain applied in 5G and related problems, reviews other blockchain-enforced network technologies, and shows how blockchain can help in services dedicated to vertical industries. Finally, it presents our vision of new blockchain applications in modern 5G networks and beyond. The new-generation networks use two fundamental technologies, slicing and virtualization, and attackers attempt to execute new types of attacks on them. In the paper, we discuss one of the possible scenarios exhibiting the shortcomings of the slicing technology architecture. We propose using blockchain technology to create new slices and to connect new or existing subscribers to slices in the 5G core network. Blockchain technology should solve these architectural shortcomings. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper Computing is a recent emerging cloud model that affords clients limitless facilities, lowers the rate of customer storing and computation and progresses the ease of use, leading to a surge in the number of enterprises and individuals storing data in the cloud. Cloud services are used by various organizations (education, medical and commercial) to store their data. In the health-care industry, for example, patient medical data is outsourced to a cloud server. Instead of relying onmedical service providers, clients can access theirmedical data over the cloud. Design/methodology/approach: This section explains the proposed cloud-based health-care system for secure data storage and access control called hash-based ciphertext policy attribute-based encryption with signature (hCP-ABES). It provides access control with finer granularity, security, authentication and user confidentiality of medical data. It enhances ciphertext-policy attribute-based encryption (CP-ABE) with hashing, encryption and signature. The proposed architecture includes protection mechanisms to guarantee that health-care and medical information can be securely exchanged between health systems via the cloud. Figure 2 depicts the proposed work's architectural design. Findings: For health-care-related applications, safe contact with common documents hosted on a cloud server is becoming increasingly important. However, there are numerous constraints to designing an effective and safe data access method, including cloud server performance, a high number of data users and various security requirements. This work adds hashing and signature to the classic CP-ABE technique. It protects the confidentiality of health-care data while also allowing for fine-grained access control. According to an analysis of security needs, this work fulfills the privacy and integrity of health information using federated learning. Originality/value: The Internet of Things (IoT) technology and smart diagnostic implants have enhanced health-care systems by allowing for remote access and screening of patients' health issues at any time and from any location. Medical IoT devices monitor patients' health status and combine this information into medical records, which are then transferred to the cloud and viewed by health providers for decision-making. However, when it comes to information transfer, the security and secrecy of electronic health records become a major concern. This work offers effective data storage and access control for a smart healthcare system to protect confidentiality. CP-ABE ensures data confidentiality and also allows control on data access at a finer level. Furthermore, it allows owners to set up a dynamic patients health data sharing policy under the cloud layer. hCP-ABES proposed fine-grained data access, security, authentication and user privacy of medical data. This paper enhances CP-ABE with hashing, encryption and signature. The proposed method has been evaluated, and the results signify that the proposed hCP-ABES is feasible compared to other access control schemes using federated learning. [ABSTRACT FROM AUTHOR]

Since the advent of networked systems, fuzzy graph theory has surfaced as a fertile paradigm for handling uncertainties and ambiguities. Among the different modes of handling challenges created by the uncertainties and ambiguities of current networked systems, integrating fuzzy graph theory with cryptography has emerged as the most promising approach. In this regard, this review paper elaborates on potentially studying fuzzy graph-based cryptographic techniques, application perspectives, and future research directions. Since the expressive power of fuzzy graphs allows the cryptographic schemes to handle imprecise information and to enhance security in many domains, several domains have benefited, such as image encryption, key management, and attribute-based encryption. The paper analyzes in depth the research landscape, mainly by focusing on the varied techniques used, such as fuzzy logic for key generation and fuzzy attribute representation for access control policies. A comparison with performance metrics unveils the trade-offs and advantages of different fuzzy graph-based approaches in efficiency, security strength, and computational overhead. Additionally, the survey explores the security applications of fuzzy graph-based cryptography and underpins potential development for secure communication in wireless sensor networks, privacy-preserving data mining, fine-grained access control in cloud computing, and blockchain security. Some challenges and research directions, such as the standardization of fuzzy logic operators, algorithmic optimization, integration with emerging technologies, and exploitation of post-quantum cryptography applications, are also brought out. This review will thus bring insight into this interdisciplinary domain and stimulate further research for the design of more robust, adaptive, and secure cryptographic systems in the wake of rising complexities and uncertainties. [ABSTRACT FROM AUTHOR]

Electronic medical records are a patient's digital asset that enhances the information available to doctors for tracking their patients' health. When this information is stored in a secure environment, health examination reports can serve as a dependable repository for thorough observation of a patient's well‐being. However, it is crucial for the owner to have control over access to these repositories. In this scenario, a blockchain ecosystem with appropriate access control mechanisms can help create a distributed and decentralized storage platform to ensure the safety and security of data. Developing cost‐effective smart contracts and creating clear design diagrams to represent them are essential for establishing such an ecosystem. This paper introduces a smart contract for the Ethereum blockchain that allows an owner to maintain control over their data. The paper presents a diagram for visually representing the modules within our smart contract, providing readers with a clearer understanding of the access control techniques utilized in implementing our strategies. Our smart contract offers clinicians a valuable means of accessing historical data to promptly evaluate a patient's health in emergency situations. We showcase its efficacy by illustrating how it streamlines insurance claims, where it verifies the patient's coverage and automatically authorizes medical expense payments. Lastly, a study is presented to showcase an effective method of storing the ingested data within the Ethereum network. The suggested approach allows restrictions on data visibility based on the viewer's accessibility through identity‐based access control achieved using additional structures in smart contracts. These structures store filtered records accessible to users based on their viewing privileges. The simulated test bed results support the efficiency of using smart contracts with additional structures in terms of gas consumption when compared to those that use a single structure for read and write operations. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a heterogeneous network composed of numerous dynamically connected devices. While it brings convenience, the IoT also faces serious challenges in data security. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography method that supports fine-grained access control, offering a solution to the IoT's security issues. However, existing CP-ABE schemes are inefficient and unsuitable for IoT devices with limited computing resources. To address this problem, this paper proposes an efficient pairing-free CP-ABE scheme for the IoT. The scheme is based on lightweight elliptic curve scalar multiplication and supports multi-authority and verifiable outsourced decryption. The proposed scheme satisfies indistinguishability against chosen-plaintext attacks (CPA) under the elliptic curve decisional Diffie–Hellman (ECDDH) problem. Performance analysis shows that our proposed scheme is more efficient and better suited to the IoT environment compared to existing schemes. [ABSTRACT FROM AUTHOR]

With the rapid development of the logistics industry and the continuous growth of e-commerce, effectively monitoring logistics warehouses has become increasingly important to ensure the security of goods and oversee activities within storage facilities. Although current surveillance systems provide a certain level of security for logistics warehouses, they still face issues such as data tampering, storage, and access management. These challenges can compromise the integrity of surveillance video data, making the system vulnerable to unauthorized access. To address these challenges, this paper proposes the implementation of blockchain-based security management and access control of video data in logistics warehouses. Specifically, the solution employs the Hyperledger Fabric consortium blockchain to execute smart contracts and store the hash values of video data, thereby detecting any tampering and enhancing the security and integrity of the data. Additionally, hybrid encryption technology is utilized to ensure the confidentiality of video data during transmission and storage. Furthermore, the solution leverages the InterPlanetary File System (IPFS) for distributed video storage. This not only increases the redundancy and accessibility of data storage but also reduces the risk of single-point failures. A Role-Based Access Control (RBAC) mechanism is also introduced to strictly manage access permissions to video data, ensuring that only authorized users can access the data, thereby effectively preventing unauthorized access and data breaches. Through a comprehensive analysis of computational and communication costs and the evaluation of blockchain performance at 100 transactions per second for different transaction volumes using Hyperledger Caliper, the results demonstrate the effectiveness and efficiency of the proposed method. Compared to current research, this solution exhibits higher security, providing a new approach for the secure management and access control of video data in logistics warehouses. [ABSTRACT FROM AUTHOR]

Verifiable outsourced attribute-based encryption (VO-ABE) enables one-to-many data sharing and fine-grained access control under lower trust, making it suitable for cloud or edge systems involving resource-constrained devices. There is no fully outsourced and fully verifiable attribute-based encryption scheme or key-policy VO-ABE scheme. Moreover, the previous VO-ABE schemes require multiple rounds of interaction or high verification costs to support verifiable outsourced key generation and verifiable outsourced encryption. To address these issues, in this paper, we propose an effective key-policy fully outsourced and fully verifiable attribute-based encryption scheme supporting verifiable outsourced key generation, encryption, and decryption simultaneously. We formally define two new properties: outsourced key generation verifiability and outsourced encryption verifiability. Analysis and simulation show that the proposed scheme performs well and is practical. All local computational overheads of the proposed scheme are constant and do not increase with the number of attributes or the complexity of access structures. [ABSTRACT FROM AUTHOR]

With technology development, the growing self-communicating devices in IoT networks require specific naming and identification, mainly provided by IPv6 addresses. The IPv6 address in the IoT network is generated by using the stateless auto address configuration (SLAAC) mechanism, and its uniqueness is ensured by the DAD protocol. Recent research suggests that IPv6 deployment can be a risky decision due to the existing SLAAC-based addressing scheme and the DAD protocol being prone to reconnaissance and denial of service (DoS) attacks. This research paper proposes a new IPv6 generation scheme with an improved secure DAD mechanism to address these problems. The proposed addressing scheme generates IPv6 addresses by taking a hybrid approach based on vendor id of medium access control (MAC) address, physical location, and arbitrary random numbers, which mitigates reconnaissance attacks by malicious nodes. To prevent the DAD process from DoS attacks, hybrid values of interface identifier (IID) are multicast instead of actual values. The proposed scheme is evaluated under reconnaissance and DoS attacks in the presence of malicious nodes. The evaluation results demonstrate that the proposed method effectively mitigates reconnaissance and DoS attacks, outperforming the EUI-64 and SEUI-64 schemes in terms of address success rate (ASR), energy consumption, and communication overhead. Specifically, the proposed method significantly reduces the average probing rate for scanning the existence of an IPv6 address, with only a 1% probing rate compared to SEUI-64's 5% and EUI-64's 100%. Furthermore, the additional communication overhead introduced by the proposed method is less than 13% and 11% compared to EUI-64 and SEUI-64, respectively. Additionally, the energy consumption required to assign an IPv6 address using the proposed method is lower by 12% and 5% when compared to EUI-64 and SEUI-64, respectively. These findings highlight the effectiveness of the proposed method in enhancing security and optimizing resource utilization in IPv6 addressing. [ABSTRACT FROM AUTHOR]

Cyberattacks pose a significant business risk to organizations. Although there is ample literature focusing on why people pose a major risk to organizational cybersecurity and how to deal with it, there is surprisingly little we know about cyber and information security decision-makers who are essentially the people in charge of setting up and maintaining organizational cybersecurity. In this paper, we study cybersecurity awareness of cyber and information security decision-makers, and investigate factors associated with it. We conducted an online survey among Slovenian cyber and information security decision-makers (N = 283) to (1) determine whether their cybersecurity awareness is associated with adoption of antimalware solutions in their organizations, and (2) explore which organizational factors and personal characteristics are associated with their cybersecurity awareness. Our findings indicate that awareness of well-known threats and solutions seems to be quite low for individuals in decision-making roles. They also provide insights into which threats (e.g., distributed denial-of-service (DDoS) attacks, botnets, industrial espionage, and phishing) and solutions (e.g., security operation center (SOC), advanced antimalware solutions with endpoint detection and response (EDR)/extended detection and response (XDR) capabilities, organizational critical infrastructure access control, centralized device management, multi-factor authentication, centralized management of software updates, and remote data deletion on lost or stolen devices) are cyber and information security decision-makers the least aware of. We uncovered that awareness of certain threats and solutions is positively associated with either adoption of advanced antimalware solutions with EDR/XDR capabilities or adoption of SOC. Additionally, we identified significant organizational factors (organizational role type) and personal characteristics (gender, age, experience with information security and experience with information technology (IT)) related to cybersecurity awareness of cyber and information security decision-makers. Organization size and formal education were not significant. These results offer insights that can be leveraged in targeted cybersecurity training tailored to the needs of groups of cyber and information security decision-makers based on these key factors. [ABSTRACT FROM AUTHOR]

Transitive signatures allow any entity to obtain a valid signature of (i , k) by combining signatures of (i , j) and (j , k) . However, the traditional transitive signature scheme does not offer fine-grained control over the combiner. To address this issue, we propose a formal definition of the attribute-based designated combiner transitive signature (ABDCTS) and its security model, where only entities whose inherent attributes meet the access policy can combine signatures. By introducing the fine-grained access control structure, control over the combiner is achieved. To demonstrate the feasibility of our primitive, this paper presents the first attribute-based designated combiner transitive signature scheme. Under an adaptive chosen-message attack, we prove its security based on the one-more CDH problem and the co-CDH problem, and that its algorithms have robustness. [ABSTRACT FROM AUTHOR]

Aims: Voluntary self-exclusion (VSE) programmes are intended to minimise gambling-related harm. They are considered effective for the individual but several weaknesses have been reported that deter individuals from enrolment. The present paper summarises opinions about and experiences with VSE strategies and assesses gaps and needs with regard to the current self-exclusion regulations and programmes in seven jurisdictions. Methods: A total of 102 representatives from various sectors (research community; addiction help and care services; prevention; regulatory bodies; gambling providers) in Finland, Germany, Italy, Massachusetts (USA), Norway, Sweden, and Victoria (Australia) were surveyed about their experiences with and opinions about VSE strategies, as well as gaps and needs of the current VSE regulations in their jurisdiction. Results: The respondents agreed on the need for and importance of VSE programmes. However, in all participating jurisdictions, VSE regulations at the time of the survey were considered insufficient, and the respondents suggested potential improvements to facilitate the exclusion process, increase utilisation and reduce gamblers' breaching VSE. Representatives of the gambling industry also emphasised the individual's responsibility. Conclusions: Individuals with gambling disorder require effective VSE programmes to cope with their addictive behaviour. To effectively reduce breaches, technical and legal solutions are necessary. This includes access controls based on complete nationwide registries, strict enforcement and preventing excluded gamblers from accessing unlicensed online operators. [ABSTRACT FROM AUTHOR]

Access control is a fundamental component of any data management system, ensuring the prevention of unauthorized data access. Within the realm of data streams, it plays a crucial role in query processing by facilitating authorized access to them. This paper introduces the StreamFilter framework, which focuses on securely processing queries with range filters over streaming data. Leveraging the Role-Based Access Control model, the StreamFilter framework enables the specification of fine-grained access policies at various levels of granularity, such as tuples and attributes, through the utilization of a bit string structure. To enhance the search operation during data stream query processing, the framework employs a distributed indexing method, constructing a set of smaller B + Tree indices rather than a single large B + Tree index. Furthermore, it seamlessly integrates access authorization evaluation with query processing, efficiently filtering unauthorized parts from the query results. The experimental results demonstrate an approximately 50% increase in efficiency for processing queries with range filters compared to the post-filtering strategy. This improvement is observed across all types of data distribution, including uniform, skew, and hyper skew. [ABSTRACT FROM AUTHOR]

As industries develop and informatization accelerates, enterprise collaboration is increasing. However, current architectures face malicious attacks, data tampering, privacy issues, and security and efficiency problems in information exchange and enterprise credibility. Additionally, the complexity of cyber threats requires integrating intelligent security measures to proactively defend against sophisticated attacks. To address these challenges, this paper introduces an intelligent and secure cloud–edge collaborative industrial information encryption strategy based on credibility assessment. The proposed strategy incorporates adaptive encryption specifically designed for cloud–edge and edge–edge architectures and utilizes attribute encryption to control access to user-downloaded data, ensuring secure information exchange. A mechanism for assessing enterprise credibility over a defined period helps maintain a trusted collaborative environment, crucial for identifying and mitigating risks from potentially malicious or unreliable entities. Furthermore, integrating intelligent threat detection and response systems enhances overall security by continuously monitoring and analyzing network traffic for anomalies. Experimental analysis evaluates the security of communication paths and examines how enterprise integrity influences collaboration outcomes. Simulation results show that this approach enhances enterprise integrity, reduces losses caused by harmful actors, and promotes efficient collaboration without compromising security. This intelligent and secure strategy not only safeguards sensitive data but also ensures the resilience and trustworthiness of the collaborative network. [ABSTRACT FROM AUTHOR]

Data trading enables data owners and data requesters to sell and purchase data. With the emergence of blockchain technology, research on blockchain-based data trading systems is receiving a lot of attention. Particularly, to reduce the on-chain storage cost, a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading platform. Moreover, the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data marketplace. In the data marketplace, it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple domains. In this paper, we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading systems. We consider a system model that consists of domain authorities, data senders, data receivers, a blockchain layer, and a cloud provider. The proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic techniques. In the proposed protocol, the outsourced data of the sender is encrypted under the target receiver's identity, and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature scheme. Therefore, data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each other. To demonstrate efficiency, we evaluate the performance of the proposed protocol and compare it with existing studies. [ABSTRACT FROM AUTHOR]

The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature as a tool to improve traffic operation and safety performance as AVs and driver-operated vehicles (DVs) coexist in a mixed-vehicle environment. This paper focuses on investigating the safety impacts of deploying AVMLs on freeways by repurposing general-purpose lanes (GPLs). Four ML strategies considering different lane positions and access controls were implemented in a traffic microsimulation under different AV market adoption rates (MARs) and traffic demand levels, and trajectories were used to extract rear-end and lane change conflicts. The time-to-collision (TTC) surrogate safety measure was used to identify critical conflicts using a time threshold dependent on the type of following vehicle. Rates of conflicts involving different vehicle types for all ML strategies were compared to the case of heterogeneous traffic. The results indicated that the rates of rear-end conflicts involving the same vehicle type as the lead and following vehicle, namely DV-DV and AV-AV conflicts, increased with ML implementation as more vehicles of the same type traveled in the same lane(s). By comparing the aggregated conflict rates, the design options that were deemed to negatively impact traffic efficiency and capacity were also found to negatively impact traffic safety. However, other ML options were found to be feasible in terms of traffic operation and safety performance, especially at traffic demand levels below capacity. Specifically, one left-side AVML with continuous access was found to have lower or comparable aggregated conflict rates compared to heterogenous traffic at 25% and 50% MARs, and, thus, it is expected to have positive or neutral safety impacts. [ABSTRACT FROM AUTHOR]

Background: Graded diagnosis and treatment, referral, and expert consultations between medical institutions all require cross domain access to patient medical information to support doctors' treatment decisions, leading to an increase in cross domain access among various medical institutions within the medical consortium. However, patient medical information is sensitive and private, and it is essential to control doctors' cross domain access to reduce the risk of leakage. Access control is a continuous and long-term process, and it first requires verification of the legitimacy of user identities, while utilizing control policies for selection and management. After verifying user identity and access permissions, it is also necessary to monitor unauthorized operations. Therefore, the content of access control includes authentication, implementation of control policies, and security auditing. Unlike the existing focus on authentication and control strategy implementation in access control, this article focuses on the control based on access log security auditing for doctors who have obtained authorization to access medical resources. This paper designs a blockchain based doctor intelligent cross domain access log recording system, which is used to record, query and analyze the cross domain access behavior of doctors after authorization. Through DBSCAN clustering analysis of doctors' cross domain access logs, we find the abnormal phenomenon of cross domain access, and build a penalty function to dynamically control doctors' cross domain access process, so as to reduce the risk of Data breach. Finally, through comparative analysis and experiments, it is shown that the proposed cross domain access control model for medical consortia based on DBSCAN and penalty function has good control effect on the cross domain access behavior of doctors in various medical institutions of the medical consortia, and has certain feasibility for the cross domain access control of doctors. [ABSTRACT FROM AUTHOR]

In the envisioned 6G landscape, data sharing is expected to become increasingly prevalent, giving rise to digital marketplaces that foster cooperation among organizations for collecting, sharing, and processing data for analysis. These marketplaces serve as connectors between data producers and consumers, empowering multi-tenancy scenarios for seamless and secure data sharing both within and outside organizations. Given that 6G networks promise ultra-low latency, enhanced connectivity, and massive data throughput, the need for robust data access control mechanisms becomes imperative. These mechanisms ensure security and trust among entities, particularly in multi-tenant environments where multiple organizations share infrastructure and data resources. In this paper, we have designed and implemented a novel access control mechanism tailored for a distributed data streaming system developed by Nokia Bell Labs. Our approach leverages fine-grained policies, dynamic enforcement, and transparency mechanisms to enhance trust between data owners and consumers. By facilitating secure multi-tenancy data sharing, our solution contributes to the seamless exchange of data across diverse entities within the next-generation communication ecosystem. We demonstrate that our proposed access control mechanism incurs minimal overhead while ensuring data confidentiality and integrity. The introduction of such advancements in data sharing markets strengthens the overall ecosystem by providing heightened transparency and enhanced control over data, promoting collaboration and innovation in the 6G era. [ABSTRACT FROM AUTHOR]

Various methods such as k-anonymity and differential privacy have been proposed to safeguard users' private information in the publication of location service data. However, these typically employ a rigid "all-or-nothing" privacy standard that fails to accommodate users' more nuanced and multi-level privacy-related needs. Data is irrecoverable once anonymized, leading to a permanent reduction in location data quality, in turn significantly diminishing data utility. In the paper, a novel, bidirectional and multi-layered location privacy protection method based on attribute encryption is proposed. This method offers layered, reversible, and fine-grained privacy safeguards. A hierarchical privacy protection scheme incorporates various layers of dummy information, using an access structure tree to encrypt identifiers for these dummies. Multi-level location privacy protection is achieved after adding varying amounts of dummy information at different hierarchical levels N. This allows for precise control over the de-anonymization process, where users may adjust the granularity of anonymized data based on their own trust levels for multi-level location privacy protection. This method includes an access policy which functions via an attribute encryption-based access control system, generating decryption keys for data identifiers according to user attributes, facilitating a reversible transformation between data anonymity and de-anonymity. The complexities associated with key generation, distribution, and management are thus markedly reduced. Experimental comparisons with existing methods demonstrate that the proposed method effectively balances service quality and location privacy, providing users with multi-level and reversible privacy protection services. [ABSTRACT FROM AUTHOR]

With the rapid expansion of global trade, the complexity and diversification of supply chains have become increasingly significant. In particular, the supply chain for hazardous materials, involving chemicals and explosives, requires stringent regulation. Managing the flow of these high-risk goods necessitates a reliable access control system to ensure safety and compliance. Traditional supply chain management systems often rely on centralized databases and record-keeping systems, which are prone to tampering and single points of failure, making them inadequate for current high-security demands. This paper combines blockchain technology with a hazardous materials supply chain model. In the blockchain network, our innovation lies in the introduction of a transaction coordinator to create transaction sets for each supply chain entity along with smart contracts to implement access control for these transaction sets. We also propose a new hazardous materials supply chain model architecture and conduct experimental verification using simulated hazardous materials supply chain data. Our experimental results show that the proposed method performs excellently in throughput and latency tests, demonstrating the potential to enhance the efficiency and security of supply chain management. [ABSTRACT FROM AUTHOR]

Organizations are adopting the Bring Your Own Device (BYOD) concept to enhance productivity and reduce expenses. However, this trend introduces security challenges, such as unauthorized access. Traditional access control systems, such as Attribute-Based Access Control (ABAC) and Role-Based Access Control (RBAC), are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and resources. This paper proposes a method for enforcing access decisions that is adaptable and dynamic, based on multilayer hybrid deep learning techniques, particularly the Tabular Deep Neural Network TabularDNN method. This technique transforms all input attributes in an access request into a binary classification (allow or deny) using multiple layers, ensuring accurate and efficient access decision-making. The proposed solution was evaluated using the Kaggle Amazon access control policy dataset and demonstrated its effectiveness by achieving a 94% accuracy rate. Additionally, the proposed solution enhances the implementation of access decisions based on a variety of resource and user attributes while ensuring privacy through indirect communication with the Policy Administration Point (PAP). This solution significantly improves the flexibility of access control systems, making them more dynamic and adaptable to the evolving needs of modern organizations. Furthermore, it offers a scalable approach to manage the complexities associated with the BYOD environment, providing a robust framework for secure and efficient access management. [ABSTRACT FROM AUTHOR]

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Cloud computing is a new paradigm in this new cyber era. Nowadays, most organizations are showing more reliability in this environment. The increasing reliability of the Cloud also makes it vulnerable. As vulnerability increases, there will be a greater need for privacy in terms of data, and utilizing secure services is highly recommended. So, data on the Cloud must have some privacy mechanisms to ensure personal and organizational privacy. So, for this, we must have an authentic way to increase the trust and reliability of the organization and individuals The authors have tried to create a way to rank things that uses the Analytical Hieratical Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). Based on the result and comparison, produce some hidden advantages named cost, benefit, risk and opportunity-based outcomes of the result. In this paper, we are developing a cloud data privacy model; for this, we have done an intensive literature review by including Privacy factors such as Access Control, Authentication, Authorization, Trustworthiness, Confidentiality, Integrity, and Availability. Based on that review, we have chosen a few parameters that affect cloud data privacy in all the phases of the data life cycle. Most of the already available methods must be revised per the industry's current trends. Here, we will use Analytical Hieratical Process and Technique for Order Preference by Similarity to the Ideal Solution method to prove that our claim is better than other cloud data privacy models. In this paper, the author has selected the weights of the individual cloud data privacy criteria and further calculated the rank of individual data privacy criteria using the AHP method and subsequently utilized the final weights as input of the TOPSIS method to rank the cloud data privacy criteria. [ABSTRACT FROM AUTHOR]

The design of a secure, intelligent laboratory that incorporates internet of things (IoT) devices and applications is a complex process. One of the main goals is to create a process monitoring system that can collect and analyze data from connected devices such as temperature and pressure sensors, smart locks, and access control systems. This system must operate in real time to ensure that equipment is within reference values. This reduces the risk of contamination and increases reliability. In addition, computer network security is paramount and it is imperative that certain measures such as encryption, multi-factor authentication, and intrusion detection systems are implemented. These measures help to ensure the safety and security of critical information and protect against potential risks. Physical security is also essential to protect scientific equipment and data. This paper provides a comprehensive overview of the critical factors involved in designing a secure, intelligent laboratory. It discusses the benefits of the integration of IoT devices and applications, and the security challenges that must be addressed. The paper also provides recommendations for designing and implementing a secure smart lab. [ABSTRACT FROM AUTHOR]