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Summary: The handoff rate and load balancing are two important issues that have a great impact on the spectrum and energy efficiency in the small‐cell networks (SCN). This paper investigates the handoff optimization in SCN with power‐domain non‐orthogonal multiple access (NOMA) that uses successive interference cancelation (SIC), considering the fairness among base stations (BSs). We study the joint base station association and power control problem by considering the motion of mobile users (MUs) and load balancing in the SCNs. Under the maximum allowable transmit power and minimum average‐rate constraints, two optimization problems are formulated using the number of associated MUs, the number of handoffs, and the transmit power of all MUs. The total power consumption minimization and the system‐wide and handoff utility maximization problems are combined into a single‐stage optimization problem through the weighted‐sum method. We solve the formulated problem using a game theory‐based algorithm and primal decomposition theory. The simulation results show that our proposed algorithm can significantly reduce the frequent handoffs and bring a fair power‐controlled BS association in SCN. [ABSTRACT FROM AUTHOR]

Door access control systems are important to protect the security and integrity of physical spaces. Accuracy and speed are important factors that govern their performance. In this paper, we investigate a novel approach to identify users by measuring patterns of their interactions with a doorknob via an embedded accelerometer and gyroscope and by applying deep-learning-based algorithms to these measurements. Our identification results obtained from 47 users show an accuracy of 90.2%. When the sex of the user is used as an input feature, the accuracy is 89.8% in the case of male individuals and 97.0% in the case of female individuals. We study how the accuracy is affected by the sample duration, finding that is its possible to identify users using a sample of 0.5 s with an accuracy of 68.5%. Our results demonstrate the feasibility of using patterns of motor activity to provide access control, thus extending with it the set of alternatives to be considered for behavioral biometrics. [ABSTRACT FROM AUTHOR]

In order to avoid the risk of patients' private information leakage, this paper puts forward a research on the protection of medical Internet private information based on double chaotic encryption algorithm. This paper analyzes the quantification of risk indicators for privacy information protection of medical Internet, establishes the risk quantification structure of health care big data according to the quantitative calculation results, and puts forward the strategy of controlling access to health care big data, configuring the risk level, describing the attributes of the system database, and realizing the privacy information protection of medical Internet under the double chaotic encryption algorithm. The experimental results show that the real identity of patients is protected to a certain extent in the protection of private information of medical internet after applying this method. Moreover, this method has high storage integrity and small storage standard deviation, and the method in this paper can effectively resist network intrusion. Therefore, it shows that this method has a good effect of protecting private information of medical Internet. [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]

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]

Indoor localization of a mobile target represents a prominent application within wireless sensor network (WSN), showcasing significant values and scientific interest. Interference, obstacles, and energy consumption are critical challenges for indoor applications and battery replacements. A proposed tracking system deals with several factors such as latency, energy consumption, and accuracy presenting an innovative solution for the mobile localization application. In this paper, a novel algorithm introduces a self-localization algorithm for mobile targets using the wake-up media access control (MAC) protocol. The developed tracking application is based on the trilateration technique with received signal strength indication (RSSI) measurements. Simulations are implemented in the objective modular network testbed in C++ (OMNeT++) discrete event simulator using the C++ programming language, and the RSSI values introduced are based on real indoor measurements. In addition, a determination approach for finding the optimal parameters of RSSI is assigned to implement for the simulation parameters. Simulation results show a significant reduction in power consumption and exceptional accuracy, with an average error of 1.91 m in 90% of cases. This method allows the optimization of overall energy consumption, which consumes only 2.69% during the localization of 100 different positions. [ABSTRACT FROM AUTHOR]

In application scenarios such as cloud storage, a symmetric algorithm can be used to encrypt massive data. However, using the symmetric operation and keys in encryption and decryption, it is very difficult to realize an efficient access control system. The asymmetric encryption algorithm ciphertext-policy attribute-based encryption (CP-ABE), as a versatile one-to-many encryption algorithm, is considered an ideal access control tool to solve the user's distrust of the service provider of cloud storage. However, in a traditional CP-ABE system, the malicious users may deliberately leak their attribute keys to others or build a decryption black box (DB) to provide illegal decryption services for benefits, while no one can determine their identities. To deal with the problems, especially the problem of tracing the DB builder, CP-ABE schemes with black-box traceability have been proposed in the past few years. But in this paper, we point out that for now, the tracing algorithms in all existing schemes actually work on an impractical assumption. That is, whenever a DB receives a decryption request, it always performs the decryption algorithm honestlycorrectly. We argue that if a DB finds the decryption request comes from the tracing algorithm, it may intentionally output incorrect decryption results to counter the tracing. Thus, we present the structural defect of the tracing algorithm applied to all known traceable CP-ABE schemes. We describe the construction of an alert decryption black box (ADB) that is capable of distinguishing a tracing ciphertext from a normal one. We also show how an ADB frustrates the tracing algorithm, and furthermore, malicious users can even apply an ADB to frame innocent users. [ABSTRACT FROM AUTHOR]

Face verification, crucial for identity authentication and access control in our digital society, faces significant challenges when comparing images taken in diverse environments, which vary in terms of distance, angle, and lighting conditions. These disparities often lead to decreased accuracy due to significant resolution changes. This paper introduces an adaptive face verification solution tailored for diverse conditions, particularly focusing on Unmanned Aerial Vehicle (UAV)-based public safety applications. Our approach features an innovative adaptive verification threshold algorithm and an optimised operation pipeline, specifically designed to accommodate varying distances between the UAV and the human subject. The proposed solution is implemented based on a UAV platform and empirically compared with several state-of-the-art solutions. Empirical results have shown that an improvement of 15% in accuracy can be achieved. [ABSTRACT FROM AUTHOR]

The attribute-based encryption (ABE) scheme is suitable for access control of ciphertext in cloud computing. Kowalczyk and Wee proposed an adaptively secure attribute-based encryption scheme that supports NC 1 circuits. However, the ciphertext length increases rapidly with the depth of the circuit, resulting in an increase of the computational complexity of the encryption and decryption algorithms. In this paper, to overcome this challenge, a ciphertext-policy ABE scheme that supports circuits with fan-in n is proposed. First, we design new pebble rules for secret sharing in circuits with fan-in n, improving the compactness of the security reduction. Then, the new secret sharing scheme is embedded in the encryption algorithm, which is the key to improving efficiency. Moreover, we prove the adaptive security of the scheme by using a piecewise guessing framework and dual-system encryption. Finally, by comparison analysis, this scheme exhibits a better performance. [ABSTRACT FROM AUTHOR]

E-documents are carriers of sensitive data, and their security in the open network environment has always been a common problem with the field of data security. Based on the use of encryption schemes to construct secure access control, this paper proposes a fusion data security protection scheme. This scheme realizes the safe storage of data and keys by designing a hybrid symmetric encryption algorithm, a data security deletion algorithm, and a key separation storage method. The scheme also uses file filter driver technology to design a user operation state monitoring method to realize real-time monitoring of user access behavior. In addition, this paper designs and implements a prototype system. Through the verification and analysis of its usability and security, it is proved that the solution can meet the data security protection requirements of sensitive E-documents in the open network environment. [ABSTRACT FROM AUTHOR]

This paper presents the work of the Medium Access Control (MAC) protocol for clustered wireless sensor networks (WSN) with High Altitude Platforms (HAPS) as the base station. To reduce energy consumption in WSN, clustering is carried out so that the sensors only send data to their respective cluster heads rather than directly to the HAPS. Unlike base stations which have a relatively fixed position and coverage, HAPS can shift horizontally, vertically, and even inclination movements which will affect the coverage of the nodes that can be covered. Therefore, an adaptive clustering algorithm was developed that can adapt to this issue. The main consideration in designing a MAC that is integrated with clustering algorithms is energy efficiency so that sensor nodes can last as long as possible. To achieve this goal the formation of clusters is based on a cost function based on the remaining energy, distance, and the number of sensor nodes in each cluster. Additionally, MAC in intra-cluster communication adopts the concept of scheduling based on the ratio between the distance and the remaining energy at the sensor node to avoid sensor nodes from idle listening, thereby saving energy. Furthermore, the sensor node behavior is modeled as consisting of four states, namely sleep, contention, back-off, and active Tx/Rx. The performance of the proposed MAC Protocol is evaluated through several simulations based on lifetime and energy consumption. In addition, simulations are carried out to test how far the HAPS can shift in position and keep all sensor nodes connected to the network. The simulation results show that the HAPS displacement tolerance of the proposed MAC protocol is better than the recommendations given by ITU-R F.1891. [ABSTRACT FROM AUTHOR]

Small perturbations can make deep models fail. Since deep models are widely used in face recognition systems (FRS) such as surveillance and access control, adversarial examples may introduce more subtle threats to face recognition systems. In this paper, we propose a practical white-box adversarial attack method. The method can automatically form a local area with key semantics on the face. The shape of the local area generated by the algorithm varies according to the environment and light of the character. Since these regions contain major facial features, we generated patch-like adversarial examples based on this region, which can effectively deceive FRS. The algorithm introduced the momentum parameter to stabilize the optimization directions. We accelerated the generation process by increasing the learning rate in segments. Compared with the traditional adversarial algorithm, our algorithms are very inconspicuous, which is very suitable for application in real scenes. The attack was verified on the CASIA WebFace and LFW datasets which were also proved to have good transferability. [ABSTRACT FROM AUTHOR]

A mobile agent is a software application that moves naturally among hosts in a uniform and non-uniform environment; it starts with one host and then moves onto the next in order to divide data between clients. The mobile paradigm is utilized in a wide assortment of medical care applications such as the medical information of a patient, the recovery of clinical information, the incorporation of information pertaining to their wellbeing, dynamic help, telemedicine, obtaining clinical data, patient administration, and so on. The accompanying security issues have grown in tandem with the complexity and improvements in mobile agent technologies. As mobile agents work in an insecure environment, their security is a top priority when communicating and exchanging data and information. Data integrity, data confidentiality and authentication, on-repudiation, denial of service, and access control, are all key security concerns with mobile agent migration. This paper proposes a Verifiable, Secure Mobile Agent Migration model, based on two polynomials (t, n), and an edge secret imparting plan with Blowfish encryption, to enable secure information transmission in clinical medical care. [ABSTRACT FROM AUTHOR]

Access Control Lists (ACL) are critical to protecting network and cyber-physical systems. Traditional firewalls mostly use reactive methods to enforce ACLs, so that new ACL updates cannot take effect immediately. In this paper, based on our previous work, we propose CPACK, an intelligent cyber-physical access control kit, which uses a smart algorithm to upgrade the ACL list. CPACK adopts a proactive way to enforce ACL and reacts to a new ACL update and network view update in real time. We implement CPACK on both Floodlight and ONOS controller. We then conduct a large number of experiments to compare CPACK with the Floodlight firewall application. The experimental results show that CPACK has a better performance than the existing Floodlight firewall application. CPACK is also integrated into the new version of Floodlight and ONOS controller. [ABSTRACT FROM AUTHOR]

Secure search is important for promoting the widespread use of cloud computing. As a common situation, when data users search for certain data from multiple data owners, searchable encryption raises the possibility of secure searches over encrypted cloud data. However, most of the existing schemes for the multi-owner model are based on asymmetric searchable encryption, which is inefficient for searching unstructured data. In addition, a Trusted Third-Party (TTP) is often required to assist in encrypting indexes or enforcing access control, which increases the cost and becomes a bottleneck to system security. To overcome these limitations, this paper proposes a secure multi-keyword ranked search scheme with access control for the multi-owner model, named MOMRS-AC. Specifically, we extend the basic secure KNN-based search scheme considering the single-owner model to an efficient multi-keyword ranked search scheme without TTP for the multi-owner model, and provide a signature algorithm to verify the search results. Also, we construct a fine-grained access control that supports recipient anonymity, large-universe and decentralized authorities. To lower the overhead of data users, we extend MOMRS-AC to support outsourcing of verification and decryption. Security and performance analyses demonstrate that MOMRS-AC is secure and efficient for the multi-owner model in practice. [ABSTRACT FROM AUTHOR]

Dispatching and Control Cloud (DCC) is a cloud platform constructed by State Grid Corporation with the technology of cloud computing. DCC has improved the overall operation and monitoring capabilities, the smart level and many other advantages of power grid. However, the development of DCC has been hampered by security and privacy issues. Secure unified identity authentication, access control and authorisation management are significant topics in DCC. To find out a solution for the topics above, we have employed some encryption schemes using the attribute-based encryption(ABE), as ABE can preserve users' privacy and achieve access control with fine grain over the encrypted information. SM9 is a kind of Chinese official standard in the field of cryptography, which contains the SM9 encryption algorithm (SM9-IBE). In this paper, an ABE scheme based on SM9-IBE is proposed, making SM9 support fine-grained access control which would be better applied in DCC. Our proposed scheme (SM9-ABE) has been proven to be of great security in the selective CPA model under DBDH assumption. Furthermore, we implement SM9-ABE and evaluate its practical performance. The implementation indicates our scheme performs well in the matter of security and functionality, at an additional time cost which is acceptable. [ABSTRACT FROM AUTHOR]

• A real-time application for secure data transmission using a different approach. • The receiver system requires a confirmation signal to perform necessary action. • Utilizing chaos dynamics for generating secret codes used in the algorithm. • The transmitted data can be a simple bit or any multimedia data of major systems. In today's technology, remote control or access is widely used in many platforms. However, the fact that remotely controlled platforms are open to external attacks or not secure enough which can have serious negative consequences. In this paper, a real-time LoRa modulation based data transmission application is achieved. The security of remotely transmitted data is not only provided with a basic encryption structure, but also a confirmation signal based transceiver system is designed in which the required process is performed only with a certain time interval. Firstly, the data to be transmitted is mixed with a secret key using XOR operation then transmitter creates a random period of time that specifies how long after the confirmation signal will be sent relative to the data signal. Hence, the entire system security is enhanced by the timing algorithm running with millisecond precision between the transceiver circuits. Encryption of the confirmation signal in a similar structure as the data signal improves security of the entire system. In this application, a PWM signal containing voltage information has been successfully transmitted in ciphered form using LoRa modulation. The designed algorithm for the receiver and transmitter circuits has been tested and verified in real time application. Experimental results show that the proposed scheme can be applied to any application-based communication system. [ABSTRACT FROM AUTHOR]

In smart grid services, electricity consumption data sharing may lead to privacy breaches and the potential for misuse of personal data. Existing data aggregation approaches mainly rely on homomorphic encryption techniques to achieve privacy protection in data sharing, however, lack consideration of controlled anonymity and fine-grained access control. This paper proposes a demand-driven privacy-preserving scheme for anonymous data sharing in smart grids to solve these problems. Specifically, an authenticable pseudonym assignment method is first proposed to achieve controlled anonymity. In addition, a proxy re-encryption technique and a data separation algorithm are implemented to achieve fine-grained access control. Finally, we strictly prove that our scheme achieves privacy protection and authentication, and demonstrate its feasibility and effectiveness through simulations. [ABSTRACT FROM AUTHOR]

Attribute-Based Signature (ABS), where messages are signed concerning a signing strategy conveyed as predicates, provides a necessary platform for implementing fine-grained access control over signed messages in an attribute-based cryptosystem. Research into ABS has seen rapid progress in recent years, and we consider it a fitting proposition to achieve anonymous authentication. Due to its unique characteristic, ABS is widely adopted in various application scenarios. Considering the fruitful and compelling prospect of ABS, it is desirable to survey the ABS systematically and thoroughly. This paper offers an exhaustive survey and examines the state-of-the-art of ABS designs and schemes. Furthermore, the survey proffers precise insights into some classic concretely constructed algorithms as well as the design philosophy behind these algorithms. Additionally, we examine the extensions (the several directions) of ABS and its advancement after its inception. We compare related work from the perspectives of performance, functionality, and security level and discuss open research issues. • Publications on Attribute-based signature since inception in 2008 to the year 2020. • A comprehensive taxonomy and state-of-the-art of Attribute-based signature schemes. • Detailed insights on some essential techniques on some classic constructed algorithms. • Extensions of Attribute-based signature and its progress since its inception. • Design principles of Attribute-based signature and comparisons between existing works. [ABSTRACT FROM AUTHOR]

In digital intelligence era, the authenticity of data and the privacy protection of data sharing and multiparty collaborative computing are key factors in building a good credit evaluation system. Although blockchain-based credit evaluation system considered this point, more studies on data privacy protection are either only the design of the framework or the proposal of the concept, which is insufficient for privacy protection. To provide a more comprehensive and reliable privacy-preserving scheme, this paper proposes a novel credit evaluation system with secure sharing and multiparty computation based on blockchain. The system consists of five modules: data, access control, data encryption, secure computation and model storage modules. The Hyperledger Fabric blockchain-based data module ensures the authenticity and traceability of the data source. The raw data are encrypted by a linear transformation algorithm in the data encryption module, which minimizes the output and utilization of data when leaving local storage and prevents potential privacy leakage in data sharing to the greatest extent. The phillie homomorphic encryption-based secure computation algorithm in the secure computation module achieves secure data sharing while applying the secure multiparty computation, which makes it possible to data sharing and privacy protection in multiparty computing. The system obtains final summary statistical results without exposing the raw data. Additionally, the final statistical results of the raw data can be inferred from the encrypted data, and their results are consistent. The correctness and accuracy of the linear conversion encryption mechanism and homomorphic encryption algorithm are proven by theoretical analysis. Security analysis and calculation case show the security of the proposed credit evaluation system and the correctness and effectiveness of the proposed encryption scheme. • A novel privacy-preserving credit evaluation system based on blockchain is proposed. • Concerns on the disclosure of commercially sensitive data are solved. • A linear transformation algorithm is used to encrypt the original data. • The data access control policy based on CP-ABE is used in access control module. • The PHE and SMPC algorithm achieve the purpose of data availability and invisibility. [ABSTRACT FROM AUTHOR]

It is difficult for wireless local area networks (WLANs), IEEE 802.11ax high-efficiency WLAN (HEW), to join next-generation innovations such as 5th generation (5G) and Internet of Things (IoT) because they still have their conventional channel access mechanism as their essential medium access control (MAC) protocol. The MAC protocol uses a traditional binary exponential backoff (BEB) algorithm to access channel resources that depend on the noncognitive increment of contention parameters for collision avoidance. In BEB, the collision issue increases with the increase in connected devices in the network due to a fixed contention window size. The larger the size of the network, the larger the collision in the network. To avoid such a circumstance, in this paper, we propose a sliding group window (sGW) mechanism dependent on collision-point assessment in order to improve the performance of MAC protocol for HEW. The proposed algorithm additionally presents a rebacking off for collision avoidance (ReBOCA) system for sGW, which combines the uniform dispersion of the contention parameters. This variation of an ordinary backoff algorithm permits the reasonable sliding of the user groups in the case of collision. The algorithm explicitly accounts for the peculiarities of dense environments and backward compatibility. Key aspects of the proposed solution include collision-point estimation, rebacking off for collision distribution convergence for fair treatment, and adaptive sliding of group windows to mitigate contention unfairness. We further formulated a closed-form Markov chain model for the performance analysis of our proposed sGW with ReBOCA scheme. Theoretical and practical results prove that our proposed scheme achieved maximal efficiency, even under dense environments. An increase in throughput with a lower packet collision probability was achieved with the proposed mechanism, and the efficiency increased as the number of contending stations increased than compared to traditional BEB performance. Our proposed ReBOCA mechanism enhanced network throughput by 38.18% than compared to the conventional BEB mechanism. [ABSTRACT FROM AUTHOR]

A Simple Temporal Network (STN) consists of time points modeling temporal events and constraints modeling the minimal and maximal temporal distance between them. A Simple Temporal Network with Decisions (STND) extends an STN to model temporal plans with decisions. STNDs label time points and constraints by conjunctions of literals saying for which scenarios (i.e., complete truth value assignments to the propositions) they are relevant. In this paper, we deal with the use of STNDs for modeling and synthesizing execution strategies. We propose an incremental hybrid SAT-based consistency checking algorithm for STNDs that is faster than the one previously proposed and allows for the synthesis of all consistent scenarios and related early execution schedules (offline temporal planning). We carry out an experimental evaluation with Kappa, a tool that we developed for STNDs. We also show that any STND can be easily translated into a disjunctive temporal network and vice versa. [ABSTRACT FROM AUTHOR]