Access Control Research Articles

B-ERAC: Blockchain-Enabled Role-Based Access Control for Secure IoT Device Communication

Security risks are increasingly concerning as the Internet of Things (IoT) expands. Authentication, access control, and authorization present significant challenges for resource-constrained IoT devices. Traditional authentication methods often require enhancements for these devices, but Blockchain technology presents a potential solution. Decentralized and distributed, Blockchain eliminates a single point of failure and relies on Elliptic Curve Cryptography (ECC) for robust security. We have introduced a cutting-edge solution to fortify communication security within IoT devices across supply chain ecosystems. By harnessing the power of Blockchain technology, our framework incorporates smart contracts, adheres to ES256 encryption standards, and seamlessly integrates with Infura API. These components establish stringent access controls, ensure data integrity, and enhance transparency throughout supply chain processes. The framework’s robust architecture facilitates swift and secure transactions, bolsters traceability efforts, and effectively mitigates potential security risks. With its scalable design and reliable functionality, this framework emerges as a pivotal asset for optimizing IoT device communication within dynamic supply chain environments. The use of ProVerif in our analysis provides a formal guarantee of the correctness of our access control mechanisms.

An efficient hierarchical attribute-based encryption scheme with cross-domain data sharing

With the rapid advancement of data sharing technology, an increasing amount of data is being stored on cloud servers. To enable fine-grained access control over the data stored on cloud servers, the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology has been widely adopted. Recognizing that shared data and files often possess a hierarchical structure, hierarchical CP-ABE technology has been proposed recently. However, most existing schemes are restricted to single-domain data access, which limits their flexibility and universal applicability in practical applications. To address this limitation, an access control scheme based on hierarchical CP-ABE, named CDS-CP-ABE, is proposed to facilitate secure and efficient cross-domain data sharing. The scheme is capable of not only realizing fine-grained hierarchical access control within a single domain but also enabling cross-domain data sharing. Security analysis confirms that our scheme effectively resists chosen-plaintext attack. Furthermore, empirical results indicate that the time consumption associated with our scheme is lower compared to other existing schemes.

Efficient security interface for high-performance Ceph storage systems

Ceph portrays a resilient clustered storage solution with supporting object, block, and file storage capabilities with no single point of failure. Despite these qualifications, data confidentiality defines a concern in the system, as authentication and access control are the only data protection security services in Ceph. CephArmor was proposed as a third-party security interface to protect data confidentiality by adding an extra protection layer to data at rest. Despite the added layer, the initial design of the API needed to be more efficient in addressing security and performance simultaneously. In this study, we propose a new architectural design to address the associated issues with the preliminary prototype. Comprehensive performance and security analysis verify the improvement of the proposed method compared to the initial approach. The benchmark result has indicated a 37% improvement on average in IOPS, elapsed time, and bandwidth for the write benchmark compared to the initial model.

A Dynamic Sandbox Detection Technique in a Private Cloud Environment

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

Web-based human-robot collaboration digital twin management and control system

Human-robot collaboration presents a promising application in customized production. The utilization of digital twin technology, an advanced form of virtual reality interaction, is pivotal in augmenting the capabilities of human-robot collaboration by enhancing perception and interaction dynamics. Human-robot collaboration digital twins have been proposed to create collaboration strategies, simulate collaborative processes, and guarantee individual safety. Nevertheless, there remain obstacles in the implementation of digital twins within human-robot collaboration. One notable challenge involves developing a user-friendly and easily accessible digital twin management and control system that is well-suited for human-robot collaboration. The human-robot collaboration digital twin is a sophisticated system that encompasses both physical and virtual environments. Effectively managing diverse resources within this system, devising collaboration strategies, and overseeing the collaboration process is essential for the standardized utilization of digital twins in human-robot collaboration. In response to the specific requirements of digital twins in this context, a web-based system has been conceptualized and implemented for managing and controlling human-robot collaboration digital twins. The system is structured based on the browser/server architecture model. Its functional design is implemented through a modular approach. The server-side database management system chosen is MySQL, while the programming and development of the control system are carried out using the Microsoft.Net Framework 4.8 on the Visual Studio 2022 platform. The system’s functional modules are exemplified through a case study on human-robot collaborative assembly. The findings of this study offer insights that can guide the standardized management and application of digital twins within the realm of human-robot collaboration.

Music-stylized hierarchical dance synthesis with user control

BackgroundSynthesizing dance motions to match musical inputs is a significant challenge in animation research. Compared to functional human motions, such as locomotion, dance motions are creative and artistic, often influenced by music, and can be independent body language expressions. Dance choreography requires motion content to follow a general dance genre, whereas dance performances under musical influence are infused with diverse impromptu motion styles. Considering the high expressiveness and variations in space and time, providing accessible and effective user control for tuning dance motion styles remains an open problem. MethodsIn this study, we present a hierarchical framework that decouples the dance synthesis task into independent modules. We use a high-level choreography module built as a Transformer-based sequence model to predict the long-term structure of a dance genre and a low-level realization module that implements dance stylization and synchronization to match the musical input or user preferences. This novel framework allows the individual modules to be trained separately. Because of the decoupling, dance composition can fully utilize existing high-quality dance datasets that do not have musical accompaniments, and the dance implementation can conveniently incorporate user controls and edit motions through a decoder network. Each module is replaceable at runtime, which adds flexibility to the synthesis of dance sequences. ResultsSynthesized results demonstrate that our framework generates high-quality diverse dance motions that are well adapted to varying musical conditions and user controls.

Access Control Models and Frameworks for the IoT Environment: Review, Challenges, and Future Direction

Access Control Models and Frameworks for the IoT Environment: Review, Challenges, and Future Direction

Design and implementation of a decentralized document management system

Digital document management systems (DMSs) can enhance organizational efficiency, security, and compliance, fostering collaboration and reducing operational costs, and are widely used for convenience and productivity. However, DMSs are vulnerable to security issues, such as unauthorized access, document forgery, and malicious insider activities. Traditional DMSs grant access permissions to individual users, which increases the risk of document leakage or manipulation when these permissions are misused. This article aims to design and implement a decentralized document management system (DDMS) that enhances the security and integrity of digital documents by decentralizing access permissions and using blockchain technology. The proposed DDMS encrypts digital documents using a symmetric key and then the key is divided and distributed among multiple users through Shamir’s secret sharing scheme. The encrypted documents are stored using the InterPlanetary file system (IPFS), ensuring integrity through content-based addressing. And blockchain-based smart contracts manage access permissions and document retrieval, ensuring access is only granted when a predefined number of participants agree. We implement our system using the Ethereum blockchain and IPFS and evaluated its performance against other types of DMSs. The experimental results demonstrate that the proposed DDMS significantly enhances security and integrity compared to three types of DMSs. While the system introduces a reasonable performance overhead, particularly with larger documents, it effectively prevents unauthorized access and tampering. For instance, the proposed system incurs approximately 12 s (1.2%) overhead when handling an 8GB document compared to the P2 system, but ensures tamper-proof access control and document integrity. As a result, the proposed DDMS addresses the critical security vulnerabilities found in conventional DMSs by decentralizing document access and leveraging blockchain and decentralized storage. This approach offers a robust solution for secure, tamper-resistant document management, making it suitable for organizations requiring high levels of confidentiality and document integrity.

A traceable and revocable decentralized attribute-based encryption scheme with fully hidden access policy for cloud-based smart healthcare

Smart healthcare is an emerging technology for enabling interaction between patients and medical personnel, medical institutions, and medical devices utilizing advanced Internet of Things (IoT) technologies. It has attracted significant attention from researchers because of the convenience of storing and sharing electronic medical records (EMRs) in the cloud. Given that a patient’s EMR contains sensitive individual information, it must be encrypted before uploading it to the cloud. As a countermeasure for data confidentiality and fine-grained access control, the Ciphertext Policy Attribute-Based Encryption (CP-ABE) technique is proposed, which helps manipulate private personal data without explicit authorization. However, most CP-ABE schemes use a centralized mechanism which may lead to performance bottlenecks and single-point-of-failure issues. They will also be at risk of key abuse and privacy breaches in smart healthcare applications. To this end, in this paper, we investigate a traceable and revocable decentralized attribute-based encryption scheme with a fully hidden access policy (TR-HP-DABE). Firstly, to overcome the issues of user privacy leakage and single-point-of-failure, a fully hidden access policy is established for multiple attribute authorities. Secondly, to prevent key abuse, the proposed TR-HP-DABE can achieve the tracking and revocation of malicious users by using Key Encryption Key (KEK) trees and updating the partial ciphertext. Furthermore, the online/offline encryption and verifiable outsourced decryption are applied to improve its efficiency in practical smart healthcare. According to our analysis, the security and traceability of TR-HP-DABE can be proved. Finally, the performance evaluation of TR-HP-DABE is more effective than some existing typical ones.

Mathematical analysis of busy tone in full-duplex optical MAC for hidden node mitigation

This article provides the mathematical analysis of carrier sense multiple access with collision avoidance (CSMA/CA) media access control (MAC) protocol of IEEE 802.15.7 optical wireless communication (OWC). While the prior works have performed the OWC CSMA/CA mathematical analysis using the Markov models, deviation from the simulation results has been observed. We address this by improving the Markov model calculations, which display a mere 0.2% throughput deviation, nearly matching the simulation results. Furthermore, we work on the hidden node problem of the OWC networks. This problem is solved in literature by using various full-duplex communication methods, such as bi-directional data transmission and the busy tone signal; the latter is employed in our previous work on full-duplex optical MAC (FD-OMAC). These techniques increase the coverage area of the nodes by utilizing an access point (AP) as a relay node. However, the AP response is delayed by the processing time, causing an unexpected network behavior. The quantitative effect of this delay remains unexplored, which is critical for optimizing the OWC network. We bridge this gap by extending the proposed Markov analysis to model CSMA/CA and the aforementioned full-duplex techniques. This work equips readers with mathematical insights for future OWC MAC layer enhancements.

Revolutionizing Cloud Security: A Novel Framework for Enhanced Data Protection in Transmission and Migration

This research introduces a novel security framework specifically tailored to enhance data protection during cloud transmission and migration. Our study addresses critical gaps in existing security models by proposing a multi-dimensional system that incorporates advanced encryption techniques, dynamic access control, and continuous security auditing. Notably, this framework excels in ensuring cloud data integrity, confidentiality, and availability—core aspects often compromised under conventional methods. Comparative analysis with existing models in simulated cloud environments reveals that our framework significantly enhances threat detection accuracy, response speed, and resource management efficiency. The findings highlight the system’s capability to reduce security vulnerabilities while optimizing operational overhead, presenting a substantial improvement over traditional security solutions. This innovative approach, marked by improved scalability and flexibility, is poised to revolutionize cloud data security practices across various industries, prompting further research into robust cloud computing security methodologies.

Enhancing attribute-based access control with Ethereum and ZK-SNARK technologies

Enhancing attribute-based access control with Ethereum and ZK-SNARK technologies

Ensuring Consistency in Interagency Government Data Exchange: A Blockchain‐based Solution

ABSTRACTEffective data exchange holds the potential to bridge information gaps between government agencies, creating essential prerequisites for enhanced collaboration. However, consistency issue often hinders the performance of interagency government data exchange. Inconsistent query results may be returned from different databases if data records are not timely synchronized, degrading mutual trust and collaboration efficiency among agencies. To address this issue, an interagency government data exchange approach is proposed. Specifically, consortium blockchain is leveraged as a write‐ahead log, enabling different agencies to trace relevant requests failed to be executed in real‐time, thereby promptly providing consistent query results. Detailed settings on protocol level are designed for the blockchain platform to facilitate data exchange regulation, including data structures, consensus algorithms and access control mechanism. Extensive simulation experiments are conducted to evaluate the performance of the proposed approach and investigate the impact of different parameters on data consistency and system availability.

Mitigating DDOS Attacks from IP-Rotating Bots Using Token-Based Access Control

Mitigating DDOS Attacks from IP-Rotating Bots Using Token-Based Access Control

A practical vehicular‐fog‐based privacy‐preserving attribute‐based keyword search system using potential games

AbstractThe growth of fog computing drives Internet of Things users to outsource data for services like storage and sharing. To ensure secure and efficient data search, extensive research has been conducted on searchable encryption, specifically attribute‐based keyword search (ABKS). ABKS facilitates precise access control over encrypted data while maintaining search functionality. However, delegating complex search operations to fog nodes introduces challenges like latency limitations, compromised search results, and unauthorized occupation of server resources. In this manuscript, we propose a Time‐Efficient Data Retrieval (TEDR) scheme to address these challenges. Our scheme incorporates two access policies, allowing data owners (DOs) and data users (DUs) to control data access and search queries. TEDR enables fog nodes to verify search queries before decryption, avoiding unnecessary decryption for invalid queries. We introduce a decentralized query submitting framework to allocate search queries among fog nodes, addressing redundancy concerns and latency issues. We analyze the decentralized query submitting game and classify it as a potential game, making it suitable for decentralized decision‐making. We evaluate TEDR performance on real‐world datasets, demonstrating practicality and efficiency. Our scheme reduces computational and communication costs by approximately 30% compared to existing methods.

Artificially Intelligent Vehicle-to-Grid Energy Management: A Semantic-Aware Framework Balancing Grid Demands and User Autonomy

As the adoption of electric vehicles increases, the challenge of managing bidirectional energy flow while ensuring grid stability and respecting user preferences becomes increasingly critical. This paper aims to develop an intelligent framework for vehicle-to-grid (V2G) energy management that balances grid demands with user autonomy. The research presents VESTA (vehicle energy sharing through artificial intelligence), featuring the semantic-aware vehicle access control (SEVAC) model for efficient and intelligent energy sharing. The methodology involves developing a comparative analysis framework, designing the SEVAC model, and implementing a proof-of-concept simulation. VESTA integrates advanced technologies, including artificial intelligence, blockchain, and edge computing, to provide a comprehensive solution for V2G management. SEVAC employs semantic awareness to prioritise critical vehicles, such as those used by emergency services, without compromising user autonomy. The proof-of-concept simulation demonstrates VESTA’s capability to handle complex V2G scenarios, showing a 15% improvement in energy distribution efficiency and a 20% reduction in response time compared to traditional systems under high grid demand conditions. The results highlight VESTA’s ability to balance grid demands with vehicle availability and user preferences, maintaining transparency and security through blockchain technology. Future work will focus on large-scale pilot studies, improving AI reliability, and developing robust privacy-preserving techniques.

Leveraging AI and ML for Next-Generation Cloud Security: Innovations in Risk-Based Access Management

In the increasing reliance on the cloud computing era, securing digital assets against sophisticated cyber threats has become a critical concern for organizations globally. Traditional security mechanisms, which often rely on static and pre-defined access control policies, must be revised to address these threats' dynamic and evolving nature. This study investigates the application of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing cloud security through the development of advanced Risk-Based Access Management (RBAM) systems. The primary objective is to evaluate how AI and ML can improve dynamic access control, threat prediction, and mitigation strategies within cloud environments. The research adopts a mixed-methods approach, combining quantitative analysis of RBAM system performance with qualitative insights from cybersecurity experts. AI/ML models were developed using extensive historical access log datasets and integrated into a cloud-based RBAM prototype. The system's performance was assessed based on its accuracy in threat detection, reduction in false positives, and effectiveness in dynamically adjusting access controls. Results indicate that the AI-enhanced RBAM system significantly outperforms traditional methods, achieving a 30% reduction in false positives and a 25% decrease in unauthorized access incidents. Additionally, AI-driven threat prediction models demonstrated high accuracy, enabling preemptive actions to mitigate potential security breaches. These findings highlight the transformative potential of AI and ML in cloud security, providing a more adaptive and proactive defense against emerging threats. The study concludes with recommendations for refining AI/ML models and exploring their application in other areas of cloud security, emphasizing the need for continued innovation to safeguard the increasingly complex digital landscapes that organizations operate within today.

Secret Sharing Schemes for Data Protection and Secure Communication: A Review

Secret sharing, also one of the significant concepts, plays a vital role in computer science for guaranteed data security and secure communication with advanced digital security demands. This paper focuses on theoretical aspects, historical development, and various schemes of secret sharing using Shamir's polynomial-based and Blakely's geometric methods. Indeed, this importance in modern security is difficult to underestimate. It is based on a comprehensive literature review and the effectiveness of schemes in access control, data storage, and secure communications. From the evaluation, it can be seen that secret sharing prevents unauthorized access and secures against single points of failure very effectively; therefore, it finds wide usage in various secure applications. From this study, it can be concluded that secret sharing is a very flexible and core tool in the field of information security with possibilities for improvement up to the challenge of developing technological threats. The nature of the problem being addressed is the increasing need for superior protection in safeguarding sensitive data in a growing digital world

The Critical Role of Role-Based Access Control (RBAC) in securing backup, recovery, and storage systems

In the contemporary digital landscape, safeguarding data through robust access control mechanisms is crucial. Role-Based Access Control (RBAC) is an effective strategy for managing access to backup and recovery systems, as well as storage devices. RBAC assigns permissions based on user roles, thereby enforcing the principle of least privilege and enhancing data security. This blog explores the significance of RBAC in these contexts and extends its relevance to ransomware and malware threats, as well as disaster recovery. Supported by scientific research and industry case studies, it underscores how RBAC can mitigate risks, ensure regulatory compliance, and improve data management practices.

Design, Development and Evaluation of Smart Lighting System for Physically Challenged Person

This study determined the effectiveness of the propose project smart home lighting system for physically disabled person. Specifically, it deals the main usage of the proposed project, its functionality, applicability, durability and safety and how this project works properly in other to help people as a new innovation. The project is tested out of 20 respondents that has knowledge regarding electricity, enough to understand the flow of the project its material used, functions, usage and how it works. The proposed project has a very good application. It helps physically disabled person to use the device even if they are alone without the help of others. Device allow users can customize lighting environment. The conclusions are drawn based on the findings of the study. Enhanced control smart lighting systems provide individuals with physical disabilities the ability to control their lights using voice commands or mobile applications. Energy efficiency often incorporate energy-saving features, such as LED bulbs and automated scheduling. Physically impaired person this device had a very important usage by providing them with convenient and accessible control over their lighting environment. Future researchers are encouraged to conduct studies similar to the present investigation in their domain school..