Explore the vast range of titles available.

Searchable encryption enables users to enjoy search services while protecting the security and privacy of their outsourced data. Blockchain-enabled searchable encryption delivers the computing processes that are executed on the server to the decentralized and transparent blockchain system, which eliminates the potential threat of malicious servers invading data. Recently, although some of the blockchain-enabled searchable encryption schemes realized that users can search freely and verify search results, unfortunately, these schemes were inefficient and costly. Motivated by this, we proposed an improved scheme that supports fine-grained access control and flexible searchable encryption. In our framework, the data owner uploads ciphertext documents and symmetric keys to cloud database and optional KMS, respectively, and manipulates the access control process and searchable encryption process through smart contracts. Finally, the experimental comparison conducted on a private Ethereum network proved the superiority of our scheme.

Electronic Health Records (EHRs) play a vital role in the healthcare domain for the patient survival system. They can include detailed information such as medical histories, medications, allergies, immunizations, vital signs, and more. It can help to reduce medical errors, improve patient safety, and increase efficiency in healthcare delivery. EHR approaches are proven to be an efficient and successful way of sharing patients’ personal health information. These kinds of highly sensitive information are vulnerable to privacy and security associated threats. As a result, new solutions must develop to meet the privacy and security concerns in health information systems. Blockchain technology has the potential to revolutionize the way electronic health records (EHRs) are stored, accessed, and utilized by healthcare providers. By utilizing a distributed ledger, blockchain technology can help ensure that data is immutable and secure from tampering. In this article, a Hyperledger consortium network has been developed for sharing health records with enhanced privacy and security. The attribute based access control (ABAC) mechanism is used for controlling access to electronic health records. The use of ABAC on the network provides EHRs with an extra layer of security and control, ensuring that only authorized users have access to sensitive data. By using attributes such as user identity, role, and health condition, it is possible to precisely control access to records on blockchain. Besides, a Gaussian naïve Bayes algorithm has been integrated with this consortium network for prediction of cardiovascular disease. The prediction of cardiovascular is difficult due to its correlated risk factors. This system is beneficial for both patients and physicians as it allows physicians to quickly identify high-risk patients and easily provide them with patient severity level using feature weight prediction algorithms. Dynamic emergency access control privileges are used for the emergency team and will be withdrawn once the emergency has been resolved, depending on the severity score. The system is implemented with the following medical datasets: the heart disease dataset, the Pima Indian diabetes dataset, the stroke prediction dataset, and the body fat prediction dataset. The above datasets are obtained from the Kaggle repository. This system evaluates system performance by simulating various operations using the Hyperledger Caliper benchmarking tool. The performance metrics such as latency, transaction rate, resource utilization, etc . are measured and compared with the benchmark.

Grid systems have huge and changeable user groups, and different autonomous domains always have different security policies. The attribute based access control (ABAC) model, which is flexible and scalable, is more suitable for Grid systems. This paper describes a method of building a flexible access control mechanism that is based on ABAC and supports multiple policies for Grid computing. Firstly an attribute based multipolicy access control model ABMAC is submitted. Compared with ABAC, ABMAC can describe multiple heterogeneous policies, and each policy is encapsulated without changing its descriptions. Then by extending the authorization architecture of XACML, the paper puts forward an authorization framework that supports ABMAC and is implemented in the Globus Toolkit release 4 (GT4) (Few parts of the authorization framework described in this paper can only be found in Globus Toolkit CVS repository. A more completed authorization framework will be appeared in the Globus Toolkit release 4.2). Basing on the concept of policy encapsulation, the framework provides a flexible and scalable authorization mechanism that can support multiple existing policies in a Grid system. The design and implementation details of GT4 authorization framework are also well discussed.

The Internet of Things (IoT) benefits our lives by integrating physical devices to the real world and offers a crucial internet infrastructure for future civilization. Because IoT devices are widely distributed and restricted in resources, it is difficult for them to adopt traditional security methods to resist malicious attacks. Unauthorized access to IoT devices, which results in severe privacy and security problems, has become a major challenge that has impeded IoT technology from being widely adopted. Therefore, the access control for IoT devices urgently needs to be improved when dealing with authorization issues. In this paper, we propose an attribute-based access control scheme that provides decentralized, flexible, and fine-grained authorization for IoT devices. Blockchain is utilized to provide authentic and reliable credentials. More importantly, a verifiable collaboration mechanism is designed to meet the needs of controlled access authorization in emergencies. Authority nodes are constructed to execute major computation tasks and interact with the blockchain. The security analysis shows that our scheme can reliably guarantee the security of authorized access. More than security assurance, a proof-of-concept prototype has been implemented to prove that our scheme is scalable, efficient, and accommodates IoT devices well.

E-health has become a top priority for healthcare organizations focused on advancing healthcare services. Thus, medical organizations have been widely adopting cloud services, resulting in the effective storage of sensitive data. To prevent privacy and security issues associated with the data, attribute-based encryption (ABE) has been a popular choice for encrypting private data. Likewise, the attribute-based access control (ABAC) technique has been widely adopted for controlling data access. Researchers have proposed electronic health record (EHR) systems using ABE techniques like ciphertext policy attribute-based encryption (CP-ABE), key policy attribute-based encryption (KP-ABE), and multi authority attribute-based encryption (MA-ABE). However, there is a lack of rigorous comparison among the various ABE schemes used in healthcare systems. To better understand the usability of ABE techniques in medical systems, we performed a comprehensive review and evaluation of the three popular ABE techniques by developing EHR systems using knowledge graphs with the same data but different encryption mechanisms. We have used the MIMIC-III dataset with varying record sizes for this study. This paper can help healthcare organizations or researchers using ABE in their systems to comprehend the correct usage scenario and the prospect of ABE deployment in the most recent technological evolution.

Auditing provides essential security control in computer systems by keeping track of all access attempts, including both legitimate and illegal access attempts. This phase can be useful in the context of audits, where eventual misbehaving parties can be held accountable. Blockchain technology can provide the trusted auditability required for access control systems. In this paper, we propose a distributed Attribute-Based Access Control (ABAC) system based on blockchain to provide trusted auditing of access attempts. Besides auditability, our system presents a level of transparency that both access requesters and resource owners can benefit from it. We present a system architecture with an implementation based on Hyperledger Fabric, achieving high efficiency and low computational overhead. The proposed solution is validated through a use case of independent digital libraries. Detailed performance analysis of our implementation is presented, taking into account different consensus mechanisms and databases. The experimental evaluation shows that our presented system can effectively handle a transaction throughput of 270 transactions per second, with an average latency of 0.54 seconds per transaction.

In traditional power grids, the unidirectional flow of energy and information has led to a decrease in efficiency. To address this issue, the concept of microgrids with bidirectional flow and independent power sources has been introduced. The components of a microgrid utilize various IoT protocols such as OPC-UA, MQTT, and DDS to implement bidirectional communication, enabling seamless network communication among different elements within the microgrid. Technological innovation, however, has simultaneously given rise to security issues in the communication system of microgrids. The use of IoT protocols creates vulnerabilities that malicious hackers may exploit to eavesdrop on data or attempt unauthorized control of microgrid devices. Therefore, monitoring and controlling security vulnerabilities is essential to prevent intrusion threats and enhance cyber resilience in the stable and efficient operation of microgrid systems. In this study, we propose an RBAC-based security approach on top of DDS protocols in microgrid systems. The proposed approach allocates roles to users or devices and grants various permissions for access control. DDS subscribers request access to topics and publishers request access to evaluations from the role repository using XACML. The overall implementation model is designed for the publisher to receive XACML transmitted from the repository and perform policy decision making and enforcement. By applying these methods, security vulnerabilities in communication between IoT devices can be reduced, and cyber resilience can be enhanced.

Large language models (LLMs) have transformed Natural Language Processing (NLP) by enabling robust text generation and understanding. However, their deployment in sensitive domains like healthcare, finance, and legal services raises critical concerns about privacy and data security. This paper proposes a comprehensive framework for embedding trust mechanisms into LLMs to dynamically control the disclosure of sensitive information. The framework integrates three core components: User Trust Profiling, Information Sensitivity Detection, and Adaptive Output Control. By leveraging techniques such as Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), Named Entity Recognition (NER), contextual analysis, and privacy-preserving methods like differential privacy, the system ensures that sensitive information is disclosed appropriately based on the user’s trust level. By focusing on balancing data utility and privacy, the proposed solution offers a novel approach to securely deploying LLMs in high-risk environments. Future work will focus on testing this framework across various domains to evaluate its effectiveness in managing sensitive data while maintaining system efficiency.

As the Internet of Things (IoT) has become prevalent, a massive number of logs produced by IoT devices are transmitted and processed every day. The logs should contain important contents and private information. Moreover, these logs may be used as evidences for forensic investigations when cyber security incidents occur. However, evidence legality and internal security issues in existing works were not properly addressed. This paper proposes an autonomous log storage management protocol with blockchain mechanism and access control for the IoT. Autonomous model allows sensors to encrypt their logs before sending it to gateway and server, so that the logs are not revealed to the public during communication process. Along with blockchain, we introduce the concept “signature chain”. The integration of blockchain and signature chain provides efficient management functions with valuable security properties for the logs, including robust identity verification, data integrity, non-repudiation, data tamper resistance, and the legality. Our work also employs attribute-based encryption to achieve fine-grained access control and data confidentiality. The results of security analysis using AVSIPA toolset, GNY logic and semantic proof indicate that the proposed protocol meets various security requirements. Providing good performance with elliptic curve small key size, short BLS signature, efficient signcryption method, and single sign-on solution, our work is suitable for the IoT.

The reliable circulation of automotive supply chain data is crucial for automotive manufacturers and related enterprises as it promotes efficient supply chain operations and enhances their competitiveness and sustainability. However, with the increasing prominence of privacy protection and information security issues, traditional data sharing solutions are no longer able to meet the requirements for highly reliable secure storage and flexible access control. In response to this demand, we propose a secure data storage and access control scheme for the supply chain ecosystem based on the enterprise-level blockchain platform Hyperledger Fabric. The design incorporates a dual-layer attribute-based auditable access control model for access control, with four smart contracts aimed at coordinating and implementing access policies. The experimental results demonstrate that the proposed approach exhibits significant advantages under large-scale data and multi-attribute conditions. It enables fine-grained, dynamic access control under ciphertext and maintains high throughput and security in simulated real-world operational scenarios.