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In smart applications, streaming IoT data is essential to building trust in sustainable IoT solutions. However, most existing systems for storing and disseminating IoT data streams lack reliability, security, and transparency, primarily due to centralized architectures that create single points of failure. To address these limitations, this research introduces TraVel, a blockchain and transfer learning-based framework for secure IoT data management. TraVel leverages decentralized IPFS storage to handle large data volumes effectively, integrating with a private Ethereum blockchain to enhance data integrity and accessibility. In the proposed scheme, the smart home () data is collected securely and accessed over the BC with a unique hash key generated on the IPFS for all the files. Self-executing Ethereum smart contracts enforce access control and verify data integrity, allowing only validated, non-malicious data to be stored. An adversarial domain adaptation (DA) learning model is employed to detect and filter malicious data before it enters the blockchain. TraVel's performance is evaluated on blockchain parameters, with simulations conducted on REMIX IDE and InterPlanetary File System (IPFS), demonstrating its reliability and scalability for secure IoT data dissemination. [ABSTRACT FROM AUTHOR]

Distributed ground stations are capable of realizing ubiquitous control of unmanned aerial vehicles (UAVs), breaking the restriction of limited network coverage of traditional central ground stations and improving the execution efficiency of complex tasks. However, with the increase of entities in the system architecture and the rapid changes in the authority of entities, the existing access control mechanism can no longer meet the needs of ubiquitous UAV tasks, and entities in the network and UAV tasks face identity spoofing, false data injection and other attacks. In this paper, we construct a blockchain-based entity access control scheme for ubiquitous UAV swarm tasks (BAC-UAV) to ensure data security and identity security during UAV task execution. Specifically, a blockchain-based UAV access control scheme is designed, in which the private cloud (PC) maintains a consortium blockchain to register and protect entities. The controller in the distributed control network and the UAV in the flight ad-hoc network (FANET) can mutually authenticate and confirm the legal identity of the entity based on the data in the blockchain. In addition, for the task, the dynamic task data group key and the dynamic identity group key are designed based on the homomorphic algorithm to secure the UAV task data and UAV identity respectively when the UAV members change in the task formation. The experimental results show that the computational costs and communication costs of BAC-UAV are reduced by approximately 21.7 % and 2.8 % , respectively, compared to the comparison methods. [ABSTRACT FROM AUTHOR]

Access control for smart contracts is the primary security mechanism for protecting users’ digital assets. However, existing solutions have defects in control granularity and flexibility, and a large number of resource-constrained blockchain nodes impose stringent and lightweight requirements on access control mechanisms. Therefore, achieving secure, efficient, and flexible access control for smart contracts has become a key issue that blockchain applications need to address. Based on the attribute-based access control model, this paper utilizes attribute-based signature (ABS) to achieve flexible and efficient access control for smart contracts. First, to solve the problem that existing ABS schemes are not suitable for resource-constrained blockchain nodes because they are mainly based on expensive bilinear pairing, a lightweight no-pairing attribute-based signature scheme called LABS is designed to make the signature size independent of the user’s attribute set and decouple the signature from the verification policy. Then, based on the LABS scheme, a smart contract-oriented access control mechanism (DSCABS) is proposed to ensure that only legitimate users whose attributes satisfy the access policy can be authorized to invoke smart contracts. Also, DSCABS supports dynamic updates of user rights and contract access policies without modifying or redeploying the smart contract. Finally, the effectiveness of the proposed scheme is verified by simulation experiments. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) has affected more than two million people of the world, and far social distancing and segregated lifestyle have to be adopted as a common solution in recent years. To solve the problem of sanitation control and epidemic prevention in public places, in this paper, an intelligent disinfection control system based on the STM32 single-chip microprocessor was designed to realize intelligent closed-loop disinfection in local public places such as public toilets. The proposed system comprises seven modules: image acquisition, spraying control, disinfectant liquid level control, access control, voice broadcast, system display, and data storage. The STM32 microcontroller is the main control chip and collects the disinfectant liquid level information and crowd density by using flow sensors, pressure and image. Single chip microcomputer enabling composite control of disinfectant concentration and liquid level through proportion integration differentiation (PID) control and logical increase/decrease ratio control. The use of the You Only Look Once (YOLO) algorithm aids in improving the accuracy of human target recognition, dynamically obtaining the crowd density, and regulating the spraying strategy. A comparison of the dynamic changes in crowd density with the user-defined crowd density threshold is performed to optimize the access control time and model parameters and obtain the optimal access control time limit. This approach enables dynamic optimization and intelligent control of the proposed full-cycle, closed-loop disinfection model for public toilets, effectively reducing the risk of virus transmission. [ABSTRACT FROM AUTHOR]

In Internet of Things (IoT) networks, identifying the primary Medium Access Control (MAC) layer protocol which is suited for a service characteristic is necessary based on the requirements of the application. In this paper, we propose Energy Efficient and Group Priority MAC (EEGP-MAC) protocol using Hybrid Q-Learning Honey Badger Algorithm (QL-HBA) for IoT Networks. This algorithm employs reinforcement agents to select an environment based on predefined actions and tasks. It makes use of Q-learning method in Honey Badger Algorithm (HBA). In this algorithm, the PAN coordinator divides the network devices into multiple subgroups based on location, energy levels and the traffic type. In group priority assignment phase, a combined metric will be derived in terms of these parameters. Then a priority will be assigned to each group based on their combined metric. From each group, the optimal number of contention nodes will be selected using hybrid QL-HBA algorithm. The fitness function is derived in terms of the number of neighbours and total traffic loads of the nodes. Then transmission slots will be allotted to the group according to their group priority. The proposed EEGP-MAC protocol is implemented in NS3. Simulation results have shown that EEGP-MAC attains 11% lesser delay, 16% lesser energy consumption with 10% higher throughput, when compared to existing QL-DGMAC protocol, in various network sizes. [ABSTRACT FROM AUTHOR]

In recent years, the hydroacoustic communication MAC (Medium Access Control) protocol has attracted wide attention. Hydroacoustic communication networks suffer from issues such as long propagation delays and rapid dynamic changes in network load, which prevent the maximization of network performance through the use of a single transmission mode. In this paper, we propose a Dynamic Switching Transmission MAC protocol called the DSTM-MAC protocol. Firstly, the protocol realizes the design of dynamic switching transmission mode by adapting to changes in network load, introduces a more accurate model for total system delay, and computes parameters such as the switching threshold L and the optimal fixed contention window. Secondly, it carries out parameter design for different transmission modes and realizes dynamic concurrent transmission based on these modes, ultimately achieving the goal of maximizing network performance improvement. Finally, experiments demonstrate that the DSTM-MAC protocol surpasses the traditional DCF protocol in terms of end-to-end delay and system throughput. [ABSTRACT FROM AUTHOR]

Big data management systems are in demand today in almost all industries, being also a foundation for artificial intelligence training. The use of heterogeneous polystores in big data systems has led to the fact that tools within the same system have different data granularity and access control models. The harmonization of these components by the security administrator and the implementation of a common access policy are now carried out by hand. This leads to an increasing number of vulnerabilities, which in turn become frequent causes of data leaks. The current situation in the field of automation and analysis of access control in big data systems reveals the lack of automation solutions for polystore-based systems. This paper addresses the problem of automated access control analysis in big data management systems. We formulate and discuss the main contradiction between the requirement of scalability and flexibility of access control and the increased workload on the security administrator, aggravated by the use of different data and access control models in system components. To solve this problem, we propose a new automated method for analyzing security policies based on a graph model, which reduces the number of potential vulnerabilities caused by incorrect management of big data systems. The proposed method uses the data lifecycle model of the system, its current settings, and the required security policy. The use of two-pass analysis (from data sources to data receivers and back) allows us to solve two problems: the analysis of the access control system for potential vulnerabilities and the check for business logic vulnerabilities. As an example, we consider the use of a developed prototype tool for security policy analysis in a big data management system. [ABSTRACT FROM AUTHOR]

Data centres have become the backbone of infrastructure for delivering cloud services. In the emerging cloud computing paradigm, virtual machine (VM) live migration involves moving a running VM across hosts without visible interruption to the client. Security vulnerabilities, resource optimization, and maintaining the quality of service are key issues in live VM migration. Maintaining security in VM live migration is one of the critical concerns. To create a secure environment, this paper proposes a live migration technique using the blowfish cryptographic algorithm for encryption and decryption, along with blockchain technology, to address challenges such as decentralization, data privacy, and VM security. The algorithms, namely key management blowfish encryption (KMBE), access control searchable encryption (ACSE), protected searchable destination server (PSDS), and key expansion blowfish decryption (KEBD), improve security in VM live migration in terms of various parameters such as data centre request servicing time, response time, and data transfer cost. The proposed technique KMBE improves migration cost ($) by 60–70%, ACSE reduces overall energy consumption (w) by 70–80%, PSDS reduces makespan (ms) by 40–50%, and KEBD improves the security in live VM migration by 30–40%. [ABSTRACT FROM AUTHOR]

The increasing number of edge layer devices connected to fog servers in fog computing environments has led to a rise in vulnerable and unauthorized actions. Implementing authorized access control with secure key management is essential to address this issue. As the traditional key management methods rely on third-party involvement, which suffers from drawbacks such as single points of failure and inconsistent key management in centralized architecture, so establishing efficient and secure key management between edge devices while ensuring effective access control is the main challenge in the digital environment. This study introduces a novel Blockchain-Based Access Control Protocol in IoT-Enabled Fog Computing (BACP-IeFC) environment for intra-network, inter-network, and mobile device communication models. The BACP-IeFC protocol eliminates the necessity for third-party intermediaries by leveraging Elliptic Curve Cryptography (ECC) for secure data sharing and hash chains for key pair generation. The BACP-IeFC protocol utilizes session keys generated by fog servers, which are securely recorded on a blockchain, ensuring robust authentication at edge devices. A Permissioned Blockchain is also used for secure key storage at the fog layer. The BACP-IeFC security has undergone comprehensive evaluation, including testing its session key (SK) security under the Real-or-Random (ROR) model, confirming its effectiveness in achieving SK security. An informal security analysis confirms the BACP-IeFC protocol resilience against known attacks. For the formal security verification, the BACP-IeFC protocol utilized the ProVerif security tool, and the results show that it is secure against major attacks. Additionally, the performance analysis of the proposed protocol using MIRACL shows a significant improvement in computation overhead, communication, storage cost, and energy consumption cost compared to existing protocols. The scalability and latency analysis of the BACP-IeFC protocol demonstrates that it supports high scalability with low latency costs. The BACP-IeFC protocol is implemented on Truffle Blockchain using Ethereum 2.0, and a lightweight Proof of Authority (PoA) consensus algorithm demonstrates that the BACP-IeFC protocol significantly outperformed existing protocols in terms of average response time for edge device registration time, authentication time, and block preparation time. [ABSTRACT FROM AUTHOR]

The Internet of Vehicles (IoV) is currently experiencing significant development, which has involved the introduction of an efficient Access Control Mechanism (ACM). Reliable access control is evolving into mandatory in order to provide security and efficient transmission within the IoV environment as the volume of vehicles equipped with connectivity continues to expand and they become more incorporated into any number of applications. The primary objective of this research is to develop an ACM for the IoV system based on the use of a Genetically Optimized Twin-Delayed Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The TD3 model modifies access policies to be in line with the current scenario using deep reinforcement learning (Deep RL) techniques. This allows vehicles to make access decisions that are intelligent about the environment in which they are performing. To prevent energy loss while the vehicle is in transit into the client system, the model also emphasizes access based on the vehicle's energy consumption (EC). Finally, with the support of the genetic algorithm (GA), the accuracy of the access control model can be improved by optimizing the high-level parameters in a manner in which they improves efficiency. In order to further enhance the model's environmental sustainability and reliability, the recommended model provides an approach that is both profound and efficient for access control in the constantly changing setting of the IoV. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things into patient monitoring devices has garnered significant attention, especially in response to the COVID-19 pandemic's increased focus on telecare services. However, Internet of Medical Things (IoMT) devices are constrained by computational power, memory, and bandwidth, making them vulnerable to security risks associated with data transmissions over public networks. Effective authentication is essential for safeguarding patient data and preventing unauthorized control of medical sensors. Existing IoMT authentication protocols frequently fall short, exposing critical vulnerabilities such as replay and impersonation attacks. This paper extends our prior work on the Improved Lightweight Authentication Protocol (ILAPU-Q), which is based on elliptic curves and the U-Quark hash function. We enhance the ILAPU-Q scheme and present a more secure authentication protocol for embedded medical devices. This enhancement relies on Ciphertext Policy-Attribute Based Encryption (CP-ABE), enabling data sources to protect information by cryptographically enforcing access policies. Implementing CP-ABE within the Telemedicine Information System framework eliminates the need for secure data transmission or storage at a dedicated location. Comprehensive security evaluations, conducted using AVISPA and Burrows-Abadi-Needham logic (BAN Logic), confirm the protocol's resilience against a broad spectrum of attacks. Moreover, performance assessments reveal significant advancements in computational efficiency, communication overhead, and storage requirements. Notably, our protocol demonstrates an efficiency improvement of approximately 95–98% over other protocols. This substantial improvement in security and performance underscores the practical value and potential of our protocol in advancing IoMT security standards. [ABSTRACT FROM AUTHOR]

Cloud computing is widely used for medical data sharing due to its convenience and scalability in data access. In practice, patients prefer to share their medical data with healthcare professionals in a controlled manner due to the sensitive information it implies. Specifically, patients often delegate data ownership to healthcare professionals for more comprehensive treatment. When patients are cured, they wish to revoke the delegation of data ownership. In this process, data security must be ensured when implementing ownership delegation revocation. However, although schemes have been proposed to support fine-grained access control, existing data-sharing systems do not meet the need for dynamic management of data ownership between doctors and patients, and the security issues posed by revocation of ownership delegation remain unexplored. In response to this problem, we propose a time-limited data ownership delegate system (DLDS system) with revocation security, which enables data owners to flexibly control data sharing according to time and user requirements. We design a time-based prefix tree that can revoke data ownership without compromising patient data privacy. To verify the validity of data ownership delegation in a privacy-preserving manner, we design a new interactive authentication method using the Paillier encryption method and inner product computation to ensure that only authorized users can access the data. Finally, the proposed scenarios were thoroughly discussed and simulated experimentally to assess their safety and effectiveness. [ABSTRACT FROM AUTHOR]

With the rapid expansion of the Internet of Things (IoT), securing devices and the data they generate has become a critical priority. This paper proposes an access control model for IoT systems that utilizes blockchain technology to maintain a comprehensive record of devices and their authorized access permissions, with smart contracts regulating access to IoT devices. The model is organized across four layers: IoT smart devices, dew, fog, and cloud. To enable access control at both global and local levels, we combine fog computing with a distributed blockchain framework and enhance it using machine learning algorithms. The model was implemented using tools such as Ganache, MyEtherWallet, the Remix compiler, Solidity programming language, and Python for AI algorithms. We evaluated the proposed model on four datasets (Kaggle, UCI, and two randomly generated datasets), assessing its performance using metrics like accuracy and F1-score, and compared it with existing approaches. The results demonstrate that our model outperforms current methods, with the SVM algorithm achieving an accuracy of 98% and an F1-score of 99%. [ABSTRACT FROM AUTHOR]

The increasing centralization of the Web raises serious concerns regarding privacy, security, and user autonomy. In response, there has been a renewed interest in the development of secure personal information management systems and a movement towards decentralization. Decentralized personal online data stores (pods) represent a revolutionary example within this movement, built on the W3C's existing guidelines – an approach exemplified by initiatives such as Solid (https://solidproject.org). In the Solid paradigm, individuals store their personal data in pods and have absolute discretion when choosing to grant access to different users and applications. A barrier to the adoption of the pod approach is the predominant reliance on centralized indexes for search functionality in current Web and Web-based systems. This paper introduces the ESPRESSO framework, which is designed to facilitate this new paradigm of large-scale searches within personal data stores while respecting the individual pod owners' data access governance. The current ESPRESSO prototype integrates access control within pod indexes to enhance distributed keyword-based search. ESPRESSO's unique contribution not only enhances search capabilities on the decentralized Web but also paves the way for future explorations in decentralized search technologies. [ABSTRACT FROM AUTHOR]

With the new personal data protection or export control regulations, the principle of least privilege is mandatory and must be applied even for system administrators. This article explores the different approaches implemented by the main operating systems (namely Linux, Windows, FreeBSD, and Solaris) to control the privileges of system administrators in order to enforce the principle of least privilege. We define a set of requirements to manage these privileges properly, striving to balance adherence to the principle of least privilege and usability. We also present a deep analysis of each administrative privilege system based on these requirements and exhibit their benefits and limitations. This evaluation also covers the efficiency of the currently available solutions to assess the difficulty of performing administrative privileges management tasks. Following the results, the article presents the RootAsRole project, which aims to simplify Linux privilege management. We describe the new features introduced by the project and the difficulties we faced. This concrete experience allows us to highlight research challenges. [ABSTRACT FROM AUTHOR]

Spectrum Resource Efficient Medium Access Control (SRE-MAC) is proposed in this work to effectively and efficiently improve access to the communication channels of a WBAN system. Initially, Sensor nodes are collected from the human figure such as pulses, body temperature, and oxygen level. Utilize a multi-objective-based clustering algorithm to categorize sensor nodes based on a range of criteria, such as energy level, proximity to the central processing unit, similarity of physiological data, and QoS from the collected data. From it, the clustering-based K-Means Algorithm & Multi objective is presented. For choosing the best cluster heads, a Sparrow Guided Teaching Learning Optimization (SG-TLO) algorithm is used. Use the Contention Phase (CP) and variable size TDMA slot allotments of the SRE-MAC protocol to distribute spectrum resources among each cluster. Utilize the SG-TLO to identify the best spectrum allocation that balances energy consumption within each cluster, maximizes channel utilization, and reduces interference. After spectrum allocation and optimization, the Transmission Phase (TP) of the SRE-MAC protocol is used by the sensor nodes within each cluster to connect with the central processing unit. The nodes switch to sleep mode during periods of inactivity to save energy and transmit their health packets during their specific assigned time slots. Data from all clusters are acquired by the CPU, which also aggregates and analyses the data. Results of data analysis are used in a kind of context, including research, healing determination, and supervision of healthcare. Utilize performance metrics, such as network throughput, energy consumption, communication reliability, and interference levels, to assess the effectiveness of the clustering and spectrum allocation algorithms. [ABSTRACT FROM AUTHOR]

Healthcare data is crucial and sensitive, as it contains absolute information about a patient's medical history, treatments, and actions; this information gets shared among the stakeholders on a routine basis. Patients' information is vital and should be kept accurate, up-to-date, and secret; it should be available only to authorized users. Most of the existing systems are centralized and may breach data privacy. This study mainly focuses on protecting the privacy and security of sensitive healthcare data while sharing with multiple stakeholders. This work presents a privacy-preserving and access-control blockchain-based framework that uses consensus-driven decentralized data management on top of peer-to-peer distributed computing platforms to ensure the privacy, security, accessibility, and integrity of healthcare data. Blockchain technology helps to protect transactions from manipulation due to its features of irreversibility and immutability. Additionally, we thoroughly examine the security requirements afforded by blockchain-enabled systems by incorporating stakeholders like patients, doctors, chemists, and pathology labs as system entities; they can only share information through a proper channel. The proposed framework has been implemented and evaluated using Hyperledger Fabric. We observe that the proposed framework reveals promising benefits in security, regulation compliance, reliability, flexibility, and accuracy. [ABSTRACT FROM AUTHOR]

Face recognition is used in many applications such as access control, automobile security, criminal identification, immigration, healthcare, cyber security, and so on. Each person has his/her own unique face, so the face can help distinguish people from each other. Feature extraction process plays a fundamental role in accuracy of face recognition, and many algorithms have been presented to extract more informative features from the face image. In this paper, an efficient texture descriptor is proposed based on local information of the face image. In the proposed method, at first, face image is split into several sub-images in such a way that each sub-image includes one of the facial parts such as eyes, nose, and lips. Second, texture features are extracted from each sub-image using a new local pattern descriptor, and then features of sub-images are concatenated to construct feature vector. Finally, the face image is compared to images in a dataset based on a similarity measure. In addition, particle swarm optimization algorithm is used to assign weight to the features of different parts of the face image. To evaluate the proposed algorithm, four face datasets, Yale, ORL, GT and KDEF, are used. Implementation results show that the proposed method outperforms recent methods in terms of accuracy, receiver operating characteristic (ROC) curve, and area under ROC curve. [ABSTRACT FROM AUTHOR]

A cluster cum classification hierarchical bit map assisted (CCHBMA) medium access control (MAC) protocol is proposed for the energy-efficient data transmission of wireless sensor networks. The proposed protocol utilizes the advantages of clustering and classification techniques to group similar nodes and efficiently allocate the wireless medium. The hierarchical bit mapping approach is used to provide aggregation-aware data transmission across the network. The dynamic scheduling algorithm adapts to changing the network conditions to improve the network performance. The proposed MAC protocol is evaluated based on simulation analysis and analytical modeling. The performance is compared to existing MAC protocols. The result analysis shows that the proposed MAC protocol shows significant improvement in energy-saving with respect to the existing protocols without compromising the packet delivery ratio. [ABSTRACT FROM AUTHOR]

To improve the data security and integrity of the outsourced data, storing multiple copies of data on multiple cloud servers is a good way. Many public Provable Data Possession (PDP) schemes in multiple cloud servers have been proposed in recent years. However, in some scenarios, the Data Owner (DO) may not want anyone (e.g. a stranger) to check the integrity of their data. Nevertheless, few schemes consider the fault's location function when the data auditing fails. Another problem is that anyone can make a challenge for the Cloud Server (CS) in the PDP schemes. Some access control strategies are necessary to reduce the waste of computation power resources of the CS. To solve these problems, we propose a certificateless and designed-verifier auditing scheme in multi-cloud storage environments. In our scheme, we utilize certificateless signature combined with a delegation key to achieve designed-verifier auditing. We design a secret Merkle Hash Tree (MHT) to locate the faults of CSs and data blocks. We utilize Zero-Knowledge Proof (ZKP) to achieve access control. Theoretical and experimental evaluation show that the proposed scheme is efficient and practical. [ABSTRACT FROM AUTHOR]

The information systems supporting business processes of organizations generate and collect a large number of records in event logs that are exploitable in process mining tasks (discovery, conformance and enhancement). Under a Big Data scenario, Process Mining as a Service (PMaaS) can be attractive for organizations to outsource the storage of event logs and the processing resources for process mining tasks to the cloud in the presence of large event logs. However, the Cloud Service Provider (CSP) may be honest but curious, thus posing security and privacy risks when event log data are sensitive or subject to data privacy laws and regulations. In this work, a cryptography-based method is presented that preserves the privacy of event log data outsourced to an untrusted CSP, which executes the process discovery task, the most common task in process mining. The method conveniently encrypts the event log on the data owner's side to enable the CSP to apply access control over the discovered models (encrypted) through proxy re-encryption. The proposed method is implemented as a software tool and validated and evaluated in terms of performance, scalability, and data utility using real medical (sensitive) data logs under recommended security levels. The results demonstrate the feasibility of the proposed approach to support Process Discovery as a Service (PDaaS), which enables privacy preservation and access control. [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]

The application of healthcare systems has led to an explosive growth in personal electronic health records (EHRs). These EHRs are generated from different healthcare institutions and stored in cloud data centers, respectively. However, data owners lose the authority to control and track their private and sensitive EHRs. In fact, data owners cannot establish rules for EHRs exchanging and sharing, nor can they verify the integrity of EHRs stored in semi-trusted clouds. Hence, an individual-centric access control framework is required to realize data access control. In this study, we construct a data access control framework, which integrates decentralized smart contracts and role-based access control (RBAC) to provide fine-grained data access control services. The key ideas of this schme includes: (1) a fine-grained access control framework for EHRs is proposed to achieve trusted access control; (2) a personalized policies definition mechanism is adopted to achieve patient-centric data access control; (3) a integrity checking mechanism for the shared EHRs is implemented to ensure the availability of medical records. Finally, we analyze the security properties of this scheme and develop a prototype system to evaluate its performance. Both theoretical analysis and experiment results demonstrate that this scheme can provide fine-grained access control and efficient integrity checking services for EHRs. [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]

The inherent challenges associated with the Internet of Things (IoT), such as vulnerability to cyber threats and privacy issues, need the development of novel solutions to ensure secure and efficient handling of data. Fog computing resolves these concerns by facilitating data processing in proximity to edge devices, minimising latency, and improving real-time decision-making. Blockchain boosts security in fog-based systems by providing a tamper-proof and transparent ledger. However, exclusively prioritising privacy in fog-based blockchains may impede the practical execution. This article presents the FogBlock Connect paradigm, which combines Fog computing and Blockchain through the implementation of a tailored Proxy Re-encryption (PRE) algorithm inspired by BBS98. This strategy guarantees enhanced data confidentiality while simultaneously upholding operational effectiveness in fog-based blockchains for Internet of Things applications. The efficiency and effectiveness of the suggested PRE algorithm over typical encryption methods are confirmed by comprehensive simulations utilising the Fobsim simulator. The FogBlock Connect paradigm entails the transmission of updates from nearby IoT devices to Fog servers for the purpose of creating and securely storing global updates, hence improving efficiency and performance. The paradigm ensures robust privacy measures, mitigates risks of single-point failures, and facilitates precise access control, establishing a basis for secure and resilient IoT applications. The CCA resistant formal security proof provides further validation for the strength and effectiveness of the suggested approach. [ABSTRACT FROM AUTHOR]

With the rapid development of medical information technology, the widespread adoption and application of electronic medical data have prompted more and more healthcare institutions to choose to store medical data in cloud servers to facilitate easier sharing. Attribute-based encryption is utilized for sharing electronic medical data to achieve fine-grained access control. However, storing access policies in plaintext can easily expose user privacy. Additionally, during the data sharing process, placing data retrieval in the cloud prevents secure and reliable searches. To address these issues, this paper proposes a blockchain-based privacy preserving and keyword-searchable scheme for medical data sharing(BPPKS). Access policies are transformed into vector-matrix form, concealing attributes within access policies to prevent the leakage of authorized user privacy information. Leveraging blockchain's transparency, tamper-resistance, and integrity verification features, smart contracts are used for retrieval and verification, enabling secure and reliable data searches while ensuring the integrity of medical data. Simultaneously, some complex decryption operations are delegated to the cloud servers, reducing the decryption load for users to a constant level. Finally, security analysis demonstrates that this scheme can withstand adaptive chosen keyword attacks (IND-CKA), and performance evaluations show higher efficiency in computation and storage aspects. [ABSTRACT FROM AUTHOR]

With the rapid emergence of smart wearable devices and sensor-enabled medical equipment, patient-related Internet of Things (IoT) data must be handled securely in the smart healthcare sector. Electronic Health Records (EHR) provide the digital version of patient health information that needs to be handled securely while meeting access control, immutability and identity management paradigms. Information is sent to the eHealth systems via a dedicated network that leverages several application domains and is built on a centralized architecture. Regrettably, peer-to-peer (P2P) communications performance suffers substantially from computing complexity. Aiming for information security in EHR, Blockchain technology has remarkable solutions that were made possible to minimize third-party dependencies and increase security. Realizing the nature of IoT sensory equipment deployed in eHealth systems, we intended to design a Blockchain-envisioned lightweight authentication scheme using Ethereum Blockchain (BeLAS). The informal and formal security research demonstrates that BeLAS has a promising security level to withstand password guessing, replay, privileged insider, and forgery attacks and is computationally efficient. The decentralized application and interaction with Ethereum Virtual Machine (EVM) were considered to design smart contracts. Our experimental results prove that implementing a Blockchain-based EHR system is secure and efficient by enabling smart contracts to minimize third-party functionalities. The testbed analysis proves the BeLAS achieves minimal GAS per Ether consumption [1 Gas(gwei) = 10 - 9 ETH] for storing the successful EHR transactions. [ABSTRACT FROM AUTHOR]

As cloud computing usage rises, ensuring secure data transmission has become crucial. This study addresses this need by proposing a multi-risk protection plan and a comprehensive cybersecurity trust model to enhance data transmission security in cloud environments. The objective is to develop a robust framework that improves stability, optimizes energy efficiency, and enhances Quality of Service (QoS). To achieve stability, we implement redundancy, failover mechanisms, and load balancing for efficient resource utilization. The cybersecurity trust model offers a dynamic framework to evaluate the reliability of cloud service providers, while the multi-risk protection scheme addresses various threats, including insider threats and data breaches, through a layered approach. Anomaly detection, intrusion detection systems, and encryption protocols further strengthen security. In our research methodology, we test the model in a simulated environment, replicating real-world data transmission scenarios. Performance metrics include throughput, latency, and risk detection accuracy. The findings demonstrate significant improvements in data transmission security, with our encryption method achieving an impressive time of 0.2 s. Overall, the multi-risk protection scheme effectively identifies and mitigates risks, promoting a more secure cloud computing ecosystem. [ABSTRACT FROM AUTHOR]

Internet of Medical Things (IoMT) have been utilized in plentiful medical institutions. Nevertheless, since the security of EMRs in IoMT cannot be guaranteed, the EMRs should be encrypted before uploading to cloud server. Public key Encryption with Keyword Search (PEKS) can help the doctors to search encrypted EMRs, but traditional PEKS algorithms cannot resist to quantum computing attacks and without considering access control. To bridge the gap, we propose an attribute-based public key searchable encryption scheme based on lattice, named AAQ-PEKS. Initially, based on the LWE hardness, we first introduce the attribute-based PEKS that can resist quantum attacks for IoMT. Secondly, we combine Attribute-based Encryption (ABE) into AAQ-PEKS to realize access control for sensitive EMRs in the IoMT. Thirdly, the computational security analysis illustrates that our scheme achieves correctness, Indistinguishability against Chosen Plaintext Attack (IND-CPA) and Indistinguishability against Chosen Keyword Attack (IND-CKA). Lastly, comprehensive performance evaluation in practice elaborates that our AAQ-PEKS is more efficient compared with other existing top-tier schemes. To conclude, our scheme has the characteristics of resisting quantum attacks and fine-grained access control for EMR in the IoMT. [ABSTRACT FROM AUTHOR]

Digital evidence processing can be more critical in the heterogeneous Internet-of-Things (IoT) paradigm due to the lack of transparency, trust, integrity, and immutability. Researchers have conducted a substantial range of research over the past few decades to improve the digital chain of custody and forensic investigation. In a digital forensic investigation, preserving the digital evidence chain of custody with end-to-end security, integrity, privacy, traceability, access control, provenance, transparency, and evidence verification presents several challenges. The present paper proposes a blockchain-based model for a smart IoT environment to address these challenges. The primary goal of this study is to ensure the integrity, confidentiality, trust, and privacy of vital digital evidence throughout the forensic investigation. We only insert or delete digital evidence after verifying the user's authentication. We have utilized a consortium blockchain-based secure system that harnesses the benefits of an interplanetary file system (IPFS) to enhance the security and integrity of digital evidence management and chain-of-custody. The proposed mechanism can achieve security, integrity, access control, immutability, and trust for a digital chain-of-custody. The integration of the Ethereum blockchain-based test network and IPFS facilitates the development, testing, and deployment of decentralized applications (dApps) with enhanced security, efficiency, and decentralization. We deployed smart contracts on Metamask and tested them on the Sepolia test network. The Ethereum network records different gas fees and transaction fees based on various timestamps, gas prices, and traffic. In different numbers and timestamps, gas prices vary between 2.50000001 Gwei and 13.559962651 Gwei. Compared to many other transactions, the reduction ranges from 10 to 20%. The proposed model provides the highest throughput, approximately 5% more transactions per second, as well as the lowest latency. [ABSTRACT FROM AUTHOR]

The massive data generated by the Internet of Things (IoT) is often outsourced to the cloud, leading to a separation between data ownership and management. Access control during the data's validity period and assured deletion once that period expires are both crucial for protecting privacy. While recent research has primarily focused on access control, assured deletion has received less attention. Existing assured deletion schemes can be classified into key-control based and cryptographic policy based methods, but to varying degrees, they have limitations such as requiring a trusted third party, high encryption overhead, lack of support for deletion verification and fine-grained access control. To address these limitations, we propose BBAD, a blockchain-based assured deletion scheme that leverages smart contracts for fine-grained access control, employs Shamir secret sharing and re-encryption for assured key deletion, and utilizes Merkle Hash Tree (MHT) for public deletion verification. Notably, BBAD eliminates the need for a trusted third party, exhibits low computational overhead, supports customizable deletion time limit, and enables offline verification of deletion for users. Our experimental comparison with two prominent alternatives, Secure Electronic-Document Self-Destructing with Identity-Based Timed-Release Encryption (ESITE) and Key-Policy Attribute-Based Encryption for Assured Deletion (AD-KP-ABE), demonstrates that BBAD reduces data processing time by over 46.5%, data deletion time by 98.4%, and deletion verification time by 99.0%. [ABSTRACT FROM AUTHOR]

Digital Twin (DT) technology empowers organizations to create virtual counterparts of their physical assets, thereby magnifying their analytical, optimization and decision-making capabilities. More specifically, the simulation capabilities of a DT generate high-quality data that not only benefit the DT owner organization, but also increase the potential of similar organizations by leveraging the DT’s capabilities when sharing its simulation results This collaborative sharing boosts the capabilities of each participating organization, fostering a collective intelligence that amplifies their competitive advantage. Nonetheless, data exchange must rigorously safeguard each organization’s data confidentiality, and access to this data must be thoroughly controlled. Thus, this paper introduces the novel concept of DT communities and proposes a hybrid access control architecture. This architecture seamlessly integrates the strengths of both Role Based Access Control (RBAC) and Organizational Based Access Control (OrBAC), facilitating secure, authorized intra- and inter-organizational information sharing in the context of Industry 5.0, combining the strengths of local DT communication and other organization’s DTs as well. Moreover, in order to show the feasibility of the approach for critical corporate organizations and their systems, in this paper we provide a proof-of-concept implementation of this architecture. To validate its functionality and efficiency, we perform a number of experimental studies showing how various entities can benefit from securely sharing DT models based on the concept of “community". [ABSTRACT FROM AUTHOR]

In the era of the Internet of Things (IoT), where technology has revolutionized our interaction with the world around us and bridged the gap between the physical and digital realms, providing an effective fine-grained access control system is paramount to safeguarding security of the IoT ecosystem. This paper introduces SecShield, a novel Software Defined Network (SDN)-based framework, particularly designed for IoT environments. SecShield operates by evaluating access requests and granting access to IoT services only when the set of defined access policies are satisfied. Utilizing the Attribute-Based Access Control (ABAC) model, SecShield specifies fine-grained access policies for IoT services and employs an algorithm for evaluating access requests. Additionally, the framework incorporates a local cache at the edge of the IoT network, enhanced with a Least Recently Used (LRU) algorithm, to optimize the process of access request evaluation. Experimental results validate the efficiency and feasibility of SecShield, positioning it as a viable solution for improving security of real-world IoT networks. [ABSTRACT FROM AUTHOR]

The ability to share Electronic Health Records (EHRs) with the right people plays a crucial role in providing on-time diagnosis. The outsourcing of private health data on the cloud, with negligible control in the hands of the data owners, poses a significant challenge for e-healthcare applications. Obtaining the owner’s consent is not just essential for data sharing but also to protect the privacy of the data being shared. With the help of Blockchain and Interplanetary File System (IPFS), this research paper proposes a purpose-based framework for obtaining dynamic consent before sharing data among healthcare providers, academicians, etc. The study develops a blockchain system on the Ethereum network to store encrypted EHRs on IPFS. This architecture allows for secure and privacy-enhanced data sharing. The proposed model demonstrates effectiveness in enhancing data security, privacy, scalability, ownership, and integrity of medical records. The cost analysis shows a negligible contract deployment cost of 0.00174363 ETH, equivalent to $2.78. The framework presents a viable solution for securing EHRs and obtaining dynamic consent, ensuring improved healthcare data management. The use of blockchain and IPFS offers a promising avenue for enhancing data security and privacy in e-healthcare applications. [ABSTRACT FROM AUTHOR]

To prevent misuse of privacy, numerous anonymous authentication schemes with linkability and/or traceability have been proposed to ensure different types of accountabilities. Previous schemes cannot simultaneously achieve public linking and tracing while holding access control, therefore, a new tool named linkable and traceable anonymous authentication with fine-grained access control (LTAA-FGAC) is offered, which is designed to satisfy: (i) access control, i.e., only authorized users who meet a designated authentication policy are approved to authenticate messages; (ii) public linkability, i.e., anyone can tell whether two authentications with respect to a common identifier are created by an identical user; (iii) public traceability, i.e., everyone has the ability to deduce a double-authentication user's identity from two linked authentications without the help of other parties. We formally define the basic security requirements for the new tool, and also give a generic construction so as to satisfy these requirements. Then, we present a formal security proof and an implementation of our proposed LTAA-FGAC scheme. [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]

With the advancement of technology, Multimedia Social Networks (MSN) have become one of the most promising platforms for managing and sharing multimedia content. The user outsources sensitive content to the Multimedia Social Networks Service Provider (MSNSP). The MSNSP accumulates data in the network, and the user can process and share content like files, audios, and videos with other users through MSN such as YouTube, Vimeo, Flicker, Google Video, Cloud Drive, and so on. Despite receiving wide attention, two main drawbacks regarding MSN platforms are user privacy and data security. Ciphertext-policy attribute-based encryption (CP-ABE) is an appealing cryptographic primitive that plays the principal role for fine-grained access control on encrypted content, thus resolving security and privacy issues smoothly. Recently, there has been a trend to design ABE schemes incorporating a variety of additional properties. In this paper, we have assimilated revocability and key-homomorphic property in ciphertext-policy attribute-based key encapsulation mechanism (CP-ABKEM). Our designs are the first to achieve these additional two properties concurrently in an attribute-based setting. We have provided two instantiations of key-homomorphic revocableCP-ABKEM - one is selective secure against chosen-plaintext attack (CPA) in the standard model under the hardness of the q-decisional bilinear Diffie-Hellman exponent (q-DBDHE) problem, while the other achieves selective CPA security in the random oracle model under the hardness of the n-multilinear decisional Diffie-Hellman (n-MDDH) problem. Furthermore, our first scheme performs better than existing similar schemes in terms of communication overhead and master secret key size. As an advanced version of CP-ABKEM, our proposal is significant and may be utilized for various privacy-preserving protocols. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is globally distributed network systems consisting of small low-cost physical sensor nodes that can sense their environment and communicate with other nodes and computers. They are particularly used for key solutions to monitoring systems such as healthcare monitoring, environmental monitoring, and remote patient monitoring and are also preferred for their vast benefits for precision agriculture, smart building, and smart home applications. Medium Access Control (MAC) schemes are vital part of IoT systems, as the network performance metrics such as throughput, end-to-end packet delay, and energy consumption mostly depend upon the MAC scheme utilized. In this paper, a new hybrid MAC protocol called as Low-Delay Hybrid Medium Access Control (LD-HMAC) for data-gathering purposes in high-density IoT networks is presented with its models and detailed performance evaluation. In the networking application area, an unmanned aerial vehicle is considered as an access point for arranging and scheduling channel access, whereas wireless sensor nodes (IoT nodes) are considered as data-gathering elements from a dense IoT networking environment. The proposed LD-HMAC combines the strengths of both TDMA and CSMA, targeting primarily dense IoT network applications. In the development stages, first the proposed LD-HMAC protocol is designed, modeled, and evaluated analytically by using Discrete-Time Markov Chain. Second, in order to validate the analytical results of the proposed model, a simulation model was developed by using the Riverbed network simulation tool. Finally, the performance results obtained are compared to those of the corresponding MDCA and CCS models referenced in Shrestha (IEEE Trans Wirel Commun 13: 4050–4065, 2014). With respect to the end-to-end delay, the proposed LD-HMAC achieves better results than those of the MDCA and CCS models for time-critical dense IoT network applications. [ABSTRACT FROM AUTHOR]

The value of data to a company means that it must be protected. When it comes to safeguarding their local and worldwide databases, businesses face a number of challenges. To systematically review the literature to highlight the difficulties in establishing, implementing, and maintaining secure databases. In order to better understand database system problems, we did a systematic mapping study (SMS). We've analyzed 100 research publications from different digital libraries and found 20 issues after adopting inclusion and exclusion criteria. This SMS study aimed to identify the most up-to-date research in database security and the different challenges faced by users/clients using various databases from a software engineering perspective. In total, 20 challenges were identified related to database security. Our results show that "weak authorization system", "weak access control", "privacy issues/data leakage", "lack of NOP security", and "database attacks" as the most frequently cited critical challenges. Further analyses were performed to show different challenges with respect to different phases of the software development lifecycle, venue of publications, types of database attacks, and active research institutes/universities researching database security. The organizations should implement adequate mitigation strategies to address the identified database challenges. This research will also provide a direction for new research in this area. [ABSTRACT FROM AUTHOR]

The supply chain forms the backbone of the modern consumer economy, weaving an intricate network of stakeholders across geographical and socioeconomic divides. While new technologies have enhanced supply chain management, the market dynamism and network complexities continue to challenge decision-makers. This study employs social network analysis and text mining to unravel technological patterns within the patent landscape of supply chain management. The analysis draws on a dataset of over 32,000 supply chain patents from Lens.org spanning 2000–2022. Network analysis reveals cooperation patterns and key players, while text mining and clustering identify five technology clusters: secure access control, manufacturing, logistics, data management, and RFID. Technology life cycle analysis indicates that secure access control, data management, and RFID have reached maturity, while logistics is still growing and manufacturing faces saturation. The findings highlight that despite maturity, these technologies warrant continued investment to resolve persistent challenges. The technology trends and maturity insights uncovered can help enterprises make informed strategic decisions by aligning R&D initiatives with technology lifecycles. This pioneering study bridges innovation research and technology management, offering a nuanced understanding of supply chain technologies. The framework presented can be extended to analyze other domains, opening avenues for further research. Overall, this study decodes the patent landscape to decode the future. [ABSTRACT FROM AUTHOR]

The standard ACE framework provides authentication and authorization mechanisms similar to those of the standard OAuth 2.0 framework, but it is intended for use in Internet-of-Things environments. In particular, ACE relies on OAuth 2.0, CoAP, CBOR, and COSE as its core building blocks. In ACE, a non-constrained entity called Authorization Server issues Access Tokens to Clients according to some access control and policy evaluation mechanism. An Access Token is then consumed by a Resource Server, which verifies the Access Token and lets the Client accordingly access a protected resource it hosts. Access Tokens have a validity which is limited over time, but they can also be revoked by the Authorization Server before they expire. In this work, we propose the Usage Control framework as an underlying access control means for the ACE Authorization Server, and we assess its performance in terms of time required to issue and revoke Access Tokens. Moreover, we implement and evaluate a method relying on the Observe extension for CoAP, which allows to notify Clients and Resource Servers about revoked Access Tokens. Through results obtained in a real testbed, we show how this method reduces the duration of illegitimate access to protected resources following the revocation of an Access Token, as well as the time spent by Clients and Resource Servers to learn about their Access Tokens being revoked. [ABSTRACT FROM AUTHOR]

Access control refers to the mechanisms and policies determining which vehicles or entities can access certain network resources, services, or information. Nevertheless, the dynamic nature of a VANET, the necessity to support a wide range of services, and the importance of protecting users' personal information make access control a challenging issue in vehicle contexts. This study presents an efficient access control scheme based on a blockchain to enhance efficiency and security in heterogeneous signcryption (AC-HSC). Additionally, the AC-HSC protocol incorporates blockchain technology for revocation transparency, allowing roadside units to efficiently verify revoked pseudo-identities without relying on a central unit. The AC-HSC effectively fulfills various security criteria, including integrity, privacy preservation, authentication, traceability, unlinkability, non-repudiation, and resistance against replay attacks. Moreover, the formal analysis carried out in a random oracle model (ROM) proves that the proposed protocol is secure against indistinguishability under chosen-ciphertext attack (IND-CCA2) under the Computational Diffie-Hellman (CDH) assumption and existential unforgeability under chosen message attack (EUF-CMA) under the Discret-Logarithm (DL) assumption. In addition, the proposed protocol effectively addresses the issue of key escrow and successfully eliminates the challenges associated with certification management. Finally, the AC-HSC protocol implemented with a free pairing demonstrates reduced computational costs by 3.57%, 50%, 53.53%, 72.22%, 32.66%, 50.90%, 3.57%, and 57.14%, respectively, and the total energy consumption of the VANET nodes in our protocol reduced by about 4.16%, 45.03%, 50.04%, 68.37%, 31.52%, 49.67%, 4.16%, and 53.68%, respectively, as compared with the existing signcryption schemes. [ABSTRACT FROM AUTHOR]

EHRs sharing systems provide a secure and efficient way for patients and doctors to share information in smart healthcare. Due to the concern about data confidentiality and authorized access, the exploitation of attribute-based encryption (ABE) is widely adopted for EHRs sharing in cloud storage. However, most ABE-based EHRs sharing system only considered unilateral access control or supported non-flexible bilateral access control. Hence, we propose a lightwight and flexible healthcare data sharing system, LiVeRe, which enables fine-grained bilateral access control and moreover supports efficient user revocation and ciphertext integrity verification for the access control property. Technically, we employ the dual-policy framework to specify the access policy and pre-decryption techniques to alleviate the computational burden, and efficient revocation of user access rights by the KUNode algorithm. We also provide formal security models and correspondingly prove its security. Moreover, we conduct experiments on the cloud to demonstrate the practicality of our LiVeRe scheme. [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]

Women's empowerment and gender equality are key goals for development and human rights. However, a significant gap still exists in achieving these twin goals. Formulating appropriate strategies for women's empowerment requires first understanding context-specific patterns and sources of disempowerment. We use data collected using a questionnaire survey from 1653 households in Rangpur and Rajshahi districts in Bangladesh. Guided by an analytic tool that measures women's empowerment, inclusion and agency (the project level Women's Empowerment in Fisheries and aquaculture Index (pro-WEFI)), and using seven empowerment indicators, we provide findings on the status of women's empowerment, participation, and engagement in aquaculture in Bangladesh. Results show that women were highly involved in making household decisions, mainly jointly with their husbands. However, data suggest a substantial gap in women's access to financial services, in participation in aquaculture activities, and in access to and control over productive capital and remuneration for aquaculture labor. Finally, despite some women achieving adequacy on some indicators, most women in fish farming households in Bangladesh lack adequacy on many of the selected indicators. [ABSTRACT FROM AUTHOR]

The rapid growth of the Internet of Things and the massive growth of sensitive data created by user equipment have headed to resilient demand for additional security and privacy measures. The data produced by the IoT devices are often sensitive & personal, which raises new concerns about security measurement. The development & adoption of IoT and the security aspects of the IoT are not going at the same pace. The future IoT architecture must emphasize enough security concerns and provides adequate measures to prevent devices/data from being accessed by unauthorized means. This work encompasses a comprehensive analysis of frameworks & models of access control for the IoT environment. In this review paper, the analysis of access control solutions is done in four parts: the first part compares various existing review articles with our work, the second part encompasses architecture-based access control mechanisms, the third part comprises access control models, and the fourth part contains few emergent solutions including blockchain-based solutions. Subsequently, prevalent solutions are mapped to vital requirements of the IoT environment. Eventually, security obligations for the IoT environment, probable challenges, and forthcoming research directions are highlighted. This research explores the growing literature on access control for IoT, emphasizing its security requirements. [ABSTRACT FROM AUTHOR]

Despite offering substantial opportunities to tailor services to consumers' wants and needs, artificial intelligence (AI) technologies often come with ethical and operational challenges. One salient instance of such challenges emerges when vulnerable consumers, consumers who temporarily or permanently lack resource access or control, are unknowingly discriminated against, or excluded from the marketplace. By integrating the literature on consumer vulnerability, AI for social good, and the calls for rethinking marketing for a better world, the current work builds a framework on how to leverage AI technologies to detect, better serve, and empower vulnerable consumers. Specifically, our AID framework advocates for designing AI technologies that make services more accessible, optimize customer experiences and journeys interactively, and to dynamically improve consumer decision-making. Adopting a multi-stakeholder perspective, we also discuss the respective implications for researchers, managers, consumers, and public policy makers. [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 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]

Previous experiments found that acceptance of saccharin by rats was reduced if they had prior experience of sucrose or some other highly palatable solution. This study tested whether such successive negative contrast (SNC) effects involve acquisition of an aversion to the new taste. In three experiments, rats were switched from sucrose exposure in Stage 1 to a less palatable solution containing a new taste in Stage 2. In Experiments 1 and 2, a novel flavor was added to a saccharin solution at the start of Stage 2. In Experiment 1, preference tests revealed a weak aversion to the added vanilla flavor in the Suc-Sacch group, while in Experiment 2 an aversion was found in the Suc-Sacch group to the salty flavor that was used, compared with controls given access either saccharin or water in Stage 1. In Experiment 3, the Suc-Quin group, given quinine solution in Stage 2, displayed a greater aversion to quinine than a Water-Quin control group. These results support the suggestion that taste aversion learning plays a role in the initial suppression of intakes in a qualitative consummatory SNC effect. However, in the light of other evidence, it seems that the unusual persistence of successive negative contrast when rats are switched from sucrose to saccharin is not due to a long-lasting reduction in the value of saccharin. [ABSTRACT FROM AUTHOR]