Data Access Control Mechanism Research Articles

Access control for trusted data sharing

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.

JCDC: A blockchain-based framework for secure data storage and circulation in JointCloud

JointCloud computing represents a new generation cloud computing paradigm, which deeply integrates the cloud resources of multiple Cloud Service Providers (CSPs) to offer tailored cloud services to users. In contrast to traditional multi-cloud environment, JointCloud environment involve data circulation among multiple CSPs. However, in JointCloud environment, CSPs are not always fully trustworthy and they may illegally infringe upon users’ data privacy and security for their own benefit. Additionally, the heterogeneity arising from different data storage formats, structures, access control, and permission management mechanisms adopted by various CSPs makes achieving unified data management in JointCloud challenging. Therefore, to ensure secure storage and efficient circulation of data within JointCloud, it is essential to prevent violations for user privacy and data ownership, shield the heterogeneity of underlying data management mechanisms across different CSPs, and establish trusted transactions between CSPs. In this paper, we propose a framework called JointCloud Data Chain (JCDC) based on JointCloud computing and blockchain for data storage and circulation, aiming to ensure secure data storage and trustworthy transactions. JCDC utilizes blockchain to record data ownership and control data circulation, while integrating storage resources from various CSPs to construct a distributed off-chain Personal Data Storage (PDS) for expanding system storage capacity. Additionally, JCDC employs Certificateless Public Key Cryptography (CL-PKC) and Proxy Re-encryption technologies for user identity management and secure data transactions. Furthermore, smart contracts are designed to enable automated data storage and sharing. We conduct a security analysis of JCDC and develop a prototype system to validate its performance and practicality. Finally, extensive experimentation and analysis demonstrate that JCDC exhibits low time latency and cost, which makes it practical.

Trusted access control mechanism for data with blockchain-assisted attribute encryption

In the growing demand for data sharing, how to realize fine-grained trusted access control of shared data and protect data security has become a difficult problem. Ciphertext policy attribute-based encryption (CP-ABE) model is widely used in cloud data sharing scenarios, but there are problems such as privacy leakage of access policy, irrevocability of user or attribute, key escrow, and trust bottleneck. Therefore, we propose a blockchain-assisted CP-ABE (B-CP-ABE) mechanism for trusted data access control. Firstly, we construct a data trusted access control architecture based on the B-CP-ABE, which realizes the automated execution of access policies through smart contracts and guarantees the trusted access process through blockchain. Then, we define the B-CP-ABE scheme, which has the functions of policy partial hidden, attribute revocation, and anti-key escrow. The B-CP-ABE scheme utilizes Bloom filter to hide the mapping relationship of sensitive attributes in the access structure, realizes flexible revocation and recovery of users and attributes by re-encryption algorithm, and solves the key escrow problem by joint authorization of data owners and attribute authority. Finally, we demonstrate the usability of the B-CP-ABE scheme by performing security analysis and performance analysis.

Blockchain and fog computing model for secure data access control mechanisms for distributed data storage and authentication using hybrid encryption algorithm

Blockchain and fog computing model for secure data access control mechanisms for distributed data storage and authentication using hybrid encryption algorithm

Traceable Attribute-Based Encryption Scheme Using BIM Collaborative Design

BIM collaborative design involves numerous participants from various specialties who create and share vast amounts of design data at different design stages to ensure the efficient transmission of design data between these specialties. It is imperative for the BIM collaborative design platform to guarantee the security of design data and effectively trace any instances of malicious leakage or tampering. Therefore, this paper proposes a traceable ciphertext-policy attribute-based encryption scheme (TCP-ABE) that formulates a dynamic data access control mechanism based on different participants and effectively tracks malicious users in the event of risks such as tampering, theft, and unauthorized access to BIM data. In this scheme, the user’s identity information is embedded into their private key as a key component, ensuring that only users who satisfy the access policy can decrypt it. The compromised private key allows for tracing of the user’s identity. Additionally, Linear Secret Sharing Scheme (LSSS) is employed as the access structure with the user’s attribute set divided into an attribute name set and an attribute value set to protect privacy by concealing the latter within the access policy. Furthermore, the scheme integrates blockchain with cloud storage as a trusted third-party storage mechanism to ensure data integrity. Finally, the TCP-ABE scheme is comprehensively evaluated by comparing its strengths and weaknesses with other algorithms. This evaluation includes a theoretical analysis of functional and computational time overhead aspects, as well as an experimental analysis of initialization time, data encryption time, and data decryption time. The scheme exhibits excellent performance across all stages and encompasses the most comprehensive functionalities, as demonstrated by the comparative analysis and experimental results.

Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

Fuzzy-enhanced adaptive multi-layered cloud security framework leveraging artificial intelligence, quantum-resistant cryptography, and fuzzy systems for robust protection

With the growing reliance on cloud computing, ensuring robust security and data protection has become a pressing concern. Traditional cryptographic methods face potential vulnerabilities in the post-quantum era, necessitating the development of advanced security frameworks. This paper presents a fuzzy-enhanced adaptive multi-layered cloud security framework that leverages artificial intelligence, quantum-resistant cryptography, and fuzzy systems to provide comprehensive protection in cloud environments. The proposed framework incorporates data encryption, access control, and intrusion detection mechanisms, with fuzzy logic systems augmenting the decision-making process for threat detection and response. The integration of artificial intelligence and quantum-resistant cryptographic techniques enhances the framework’s adaptability and resilience against emerging threats. The implementation of fuzzy systems further improves the accuracy and efficiency of the security mechanisms, ensuring robust protection in the face of uncertainty and evolving attack vectors. The fuzzy-enhanced adaptive multi-layered cloud security framework offers a comprehensive, adaptable, and efficient solution for securing cloud infrastructures, safeguarding sensitive data, and mitigating the risks associated with the post-quantum era.

Decentralized Data Access Control Mechanism for Healthcare Sector based on Blockchain Security

Decentralized Data Access Control Mechanism for Healthcare Sector based on Blockchain Security

IAM-BDSS: A Secure Ciphertext-Policy and Identity- Attribute Management Data Sharing Scheme Based on Blockchain

Abstract: This paper presents a Ciphertext-policy attribute-based encryption (CP-ABE) is widely recognized as a secure access control mechanism for data sharing. However, the generation of secret keys (SK) in most CP-ABE schemes relies on a centralized authority (CA), which can result in high costs for establishing trust and pose a single point of failure. To address these challenges and leverage the characteristics of blockchain technology, several blockchain-based schemes have been proposed to prevent data disclosure and protect user privacy attributes. In this paper, we propose IAM-BDSS, a novel CP-ABE identity-attribute management data sharing scheme based on blockchain, aimed at ensuring privacy through hidden policies and attributes. Additionally, we introduce a transaction structure to ensure the traceability of parameter transmission within the blockchain system. Through experimental results and security analysis, we demonstrate the effectiveness and feasibility of IAMBDSS.

Data Leakage Detection using Cloud Computing

Abstract: "Data Leakage Detection Using Cloud Computing" is a project that aims to address the growing need to protect sensitive data from unauthorized access and leakage in cloud computing environments. With the increasing use of cloud-based services, there is a growing concern about data privacy and security. The project proposes a solution that leverages cloud computing technology to detect and prevent data leakage in real-time .The proposed system employs data classification, access control, and monitoring mechanisms to prevent unauthorized data access and ensure data privacy. The system is designed to monitor user activities and detect any suspicious behavior that may indicate a potential data leak. The system uses machine learning algorithms to detect anomalies in user behavior and classify data based on its sensitivity level. The system then applies access control policies to restrict user access to sensitive data.

SparkAC: Fine-Grained Access Control in Spark for Secure Data Sharing and Analytics

With the development of computing and communication technologies, an extremely large amount of data has been collected, stored, utilized, and shared, while new security and privacy challenges arise. Existing access control mechanisms provided by big data platforms have limitations in granularity and expressiveness. In this article, we present SparkAC, a novel access control mechanism for secure data sharing and analysis in Spark. In particular, we first propose a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">purpose-aware access control</i> (PAAC) model, which introduces new concepts of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">data processing purpose</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">data operation purpose</i> and an automatic purpose analysis algorithm that identifies purposes from data analytics operations and queries. Moreover, we develop a unified access control mechanism that implements PAAC model in two modules. GuardSpark++ supports structured data access control in Spark Catalyst and GuardDAG supports unstructured data access control in Spark core. Finally, we evaluate GuardSpark++ and GuardDAG with multiple data sources, applications, and data analytics engines. Experimental results show that SparkAC provides effective access control functionalities with very small (GuardSpark++) or medium (GuardDAG) performance overhead.

An Authentication and Access Control Model for Healthcare based Cloud Services

Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our suggested solution is to maintain a secure authentication and access control mechanism for health cloud data. Thus, in this work, Security Secret Key Provider (SSKP) phase is proposed for the E-healthcare-based cloud that consists of two parts. The first is an authentication scheme that is Security Secret Key (SSK) and the second is a modular access control mechanism. We explain the methodology of the proposed approach through appropriate evaluation results, which improves system security and performance by minimizing the time spent to get authentication and access the data. Simulation results indicate that our approach is significantly more effective than existing research.

Multilayer privacy‐preserving model for security and privacy access control in edge computing

SummaryIn a recent scenario of a computing environment, the Internet of Things (IoT) provides a greater impact in several applications and services. For that Edge Computing techniques are effectively incorporated, in which the sensitive data are stored on servers. As a result, edge computing allows for data storage and operation at the network's edge to emerge as optimistic advancement. Regardless, the distinctive characteristics of edge computing including real‐time computing, content perception and parallel processing have introduced a number of innovative challenges in the domain of privacy preservation and data security. Edge computing provides an extension of the cloud for designing and deploying new security resolutions in the area of IoT. In this paper, a Trusted Platform Module with Ciphertext‐policy attribute‐based encryption technique is introduced to provide a solution to a multilayer privacy‐preserving model for efficient data storage. The developed model is adaptable and has a reliable data access control mechanism. Further, the results of the experiments demonstrate that the suggested technique operates better and give 83% results in terms of storage cost, load testing, effective runtime execution, higher security, credibility, and efficiency.

Research on big data access control mechanism

Research on big data access control mechanism

Research on big data access control mechanism

Research on big data access control mechanism

FGAC: A Fine-Grained Access Control Framework for Supply Chain Data Sharing

With the rapid development of digital economics, a large number of data have been accumulated in the supply chain system, and data islands have appeared. Data sharing is an imperative way to unlock the data value of a supply chain system. A safe and effective access control mechanism for privacy-sensitive data is key in data sharing. At present, traditional access control mechanisms are static, single-factor control, and prone to a single point of failure. For dealing with these, a fine-grained access control (FGAC) framework for supply chain data sharing is proposed, based on the blockchain Hyperledger Fabric. It augments role-based access control (RBAC) by giving different attribute keywords to different types of users. This framework is implemented in smart contract Chaincodes and quantitatively verified by using the model-checking tool UPPAAL. The experiment results show that the FGAC framework enhances the efficiency and safety in the process of data sharing for the supply chain system, compared with the existing works.

A study on the big data scientific research model and the key mechanism based on blockchain

Abstract In an era of open data sharing, the scientific research field puts forward an urgent need for the value of big data. However, big data still form “data islands,” which seriously affects the level of scientific research and the progress of scientific research. In this regard, this article proposes the research and realization of the big data scientific research model and key mechanism based on blockchain. This article uses the K-means algorithm to cluster scientific research data and reasonably utilizes the decentralization, smart contracts, and non-tampering characteristics of the blockchain to design a distributed data model based on the blockchain. This article proposes that a BIZi network is formed based on a blockchain Interplanetary File System (IPFS) and Zigzag code (blockchain, IPF Sand Zigzag code, BIZi for short) to achieve reliable data connection and through a set of data access control mechanisms and data service customization mechanism to effectively provide data requirements for scientific research. Finally, IPFS network transmission speed performance can better meet the needs of scientific research. The larger the number of file blocks, the higher the fault tolerance rate of the scheme and the better the storage efficiency. In a completely open data-sharing scenario, the fault tolerance rate of Byzantine nodes is extremely high to ensure the stability of the blockchain. The current optimal consensus algorithm fault tolerance rate reaches 49%.

Data Access Control Based on Blockchain in Medical Cyber Physical Systems

The current medical cyber physical systems involve a wide range of institutions and a large number of participants. Data sharing among distributed medical institutions is already a development trend. However, the security is worrying; e.g., the access to medical data lacks uniformity and standardization. What is more, data is easy to be tampered with and leaked. This has a very negative impact on the medical industry. Therefore, a strict and reliable access control mechanism for data in the medical cyber physical systems is a prerequisite for ensuring the implementation of modern medical functions. We deal with how to design effective access control in medical cyber physical systems. Combined with blockchain technology, we design the medical cyber physical systems based on blockchain data access control mechanism and unite data in the chain of union Fabric network resources access control. We qualitatively classify medical data, define the weight level of different data, design a medical data access framework based on blockchain, build an applicable model, formulate access control strategy, and specify the role assignment and access task matching of users, so as to achieve secure and effective data access control. The Hyperledger Fabric network is established as the alliance chain for managing access control rights distribution through smart contracts so as to achieve case-based medical data access control under the blockchain.

Secure Storage of Electronic Health Records on Cloud Using Integrity Verification Auditing

Health care facilities have tried to keep sensitive patient information safe. Health information is important in identifying any stage of treatment. However, such information should be kept confidential and only available at health care facilities. To ensure data availability, health care data is now stored in the cloud and accessible online. But, this approach poses many threats due to the possibility of a patient data to be accessed by unauthorized personnel. Moreover, the standard data access control mechanisms are insufficient to ensure integrity of data due to numerous users. The constant adjustment of privileges also affected confidentiality. This paper proposes a novel approach in which the sensitive patient data in Electronic Health Records is hidden and stored more securely in the cloud. It uses a sanitization technique to detect sensitive data in the EHR and make use of identity based shared data integrity auditing to allow authorized access to the data. The web based application which uses the proposed technique is developed and tested to demonstrate its effectiveness.

Secure and Energy Efficient Data Transmission Model for WSN

Wireless sensor networks (WSNs) have been used in numerous delicate checking, observation, and surveillance systems that use sensitive data. When a WSN utilizes various data clustering techniques, data is moved to the cluster head (CH) of the corresponding cluster area. Cluster Head further communicates the information to the sink node. In a WSN, a network owner (NO) does not validate a sensor before connecting to the network, so faulty nodes may likely attach to the network to sense the data and attempt to release the information to unauthorized persons. Further, a malicious node may become a mobile node (MN) equipped to send all of a particular cluster area’s perceived data to unauthorized persons. The above-stated problems can be solved by introducing an authentication mechanism into wireless sensor networks. In this mechanism, at whatever point of time a sensor connects with a cluster region, the identity of the sensor must be validated and authenticate to, in turn, validate a mobile node. The perceived data are encrypted and then transmitted through the WSN’s transmission medium. However, the encrypted data are prone to flaws, and attackers can gain access to it illegitimately. In this study, a more energy effective and proficient secured model is proposed called a data transmission model. The technical components, including the data access control mechanism and various private key cryptography algorithms, are compared to choose the optimal energy-efficient cryptography algorithm. The proposed model is verified by experiments for encryption and decryption processes using JAVA language with advanced encryption standard (AES), data encryption standard (DES), Triple DES, Rivest Cipher (RC4), and Blowfish algorithms. The encryption time is determined using mathematical equations. The experiment results showed that the Blowfish algorithm was comparatively more energy effective than the other private key cryptography algorithms.