Access Control Method Research Articles

An Access Control Method Against Unauthorized and Noncompliant Behaviors of Real-Time Data in Industrial IoT

There is a large amount of real-time data, e.g. measurement data and instructions, among controllers, sensors, and actuators in the industrial IoT. These data are vulnerable to unauthorized access and tampering. In addition, once the controller is controlled by malicious code, it may send out dangerous instruction that is not compliant with the preset control process, which seriously interferes with the industrial control process. To achieve correct and undisturbed control based on real-time data, we propose an attribute-based access control method for real-time data in the industrial IoT to mitigate unauthorized access and tampering, and noncompliant operation. First, we analyze the abnormal behaviors of real-time data interaction in the industrial IoT. Second, we propose the multi-level hash identity authentication method to identify and block unauthorized access and tampering with real-time data. And then we model the timing relationship and task logic relationship of the control process into the attribute fields of the attribute-based access control method to identify and block non-compliant operations. Further, we design an access control module and display the lightweight deployment under the availability constraints of the control service. Finally, the proposed access control method is analyzed, proved, and experimented with. The results show that the proposed method can prevent unauthorized and non-compliant behaviors to field real-time data, meanwhile, it has a controllable delay and better scalability.

ИННОВАЦИОННЫЕ ТЕХНОЛОГИИ АУТЕНТИФИКАЦИИ И УПРАВЛЕНИЯ ДОСТУПОМ

The scientific article explores innovative authentication and access control technologies in the modern information society. The article analyzes the existing authentication and access control methods, as well as examines the latest trends and developments in this area. Special attention is paid to the use of biometric data, machine learning and artificial intelligence to ensure the safety and convenience of users. The article also discusses the advantages, challenges and prospects of using innovative authentication and access control technologies in various fields, including information security, financial services, healthcare and others.

Ensuring data confidentiality and integrity in edge computing environments : A security and privacy perspective

This study examines, from a security and privacy standpoint, the significant obstacles to maintaining data integrity and confidentiality in edge computing contexts. Data security at the edge becomes critical as more and more edge devices proliferate and generate large volumes of sensitive data. The review of the literature looks at edge computing security problems that currently exist and discusses fixes to protect data integrity and confidentiality. The article explores various vulnerabilities, emphasizing the necessity for strong security systems, including data exposure risks and integrity concerns. It examines secure communication protocols, access control methods, and encryption techniques as crucial risk-reduction instruments. Anonymization and differential privacy are two privacy-preserving techniques that are investigated to find a middle ground between user privacy and data value. The article provides real-world insights through case studies and actual implementations, and it lays out metrics and evaluation criteria for determining how successful security measures are. Finally, the report highlights the need of addressing data security in changing edge computing settings and offers future directions and research difficulties.

Application of Hierarchical Protection Security Mechanism in Database to Party Building in Colleges and Universities

Abstract With the deepening of digital development, the security protection of databases becomes more important while carrying out the digital transformation of party-building work in colleges and universities. In this study, for the database security in the party building work in colleges and universities, the protection framework of database security protection and the database hierarchical protection system based on the party building work in colleges and universities are constructed according to the needs of data hierarchical security protection. Then, on the basis of the intrusion tolerance mechanism, a database security monitoring system is established using a voting algorithm, and a multilevel information access control method is proposed for hierarchical protection. On this basis, an encryption protection mechanism based on the RSA algorithm is proposed for the sensitive information in the database of university party-building work. Through the empirical analysis of the security mechanism of counterattack protection of the university party building database, it is known that the security of the system in this paper and the probability of normal operation are both greater than 99%, and the likelihood of danger is 0.000002%. In the application of party building work, the data security of the three kinds of business is still maintained above 99.6%. The encryption time consumed is not more than 525ms, which shows that the database hierarchical protection security mechanism system constructed in this paper can meet the requirements of database security in the party building work in colleges and universities and provide a reliable guarantee for the security of the party building work database.

An image partition security-sharing mechanism based on blockchain and chaotic encryption.

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.

A Method of Network Access Control for Ensuring Network Infrastructure Security Based on Severing Superfluous Network Connectivity

A Method of Network Access Control for Ensuring Network Infrastructure Security Based on Severing Superfluous Network Connectivity

Smart Contract-Based Access Control Framework for Internet of Things Devices

The Internet of Things (IoT) has recently attracted much interest from researchers due to its diverse IoT applications. However, IoT systems encounter additional security and privacy threats. Developing an efficient IoT system is challenging because of its sophisticated network topology. Effective access control is required to ensure user privacy in the Internet of Things. Traditional access control methods are inappropriate for IoT systems because most conventional access control approaches are designed for centralized systems. This paper proposes a decentralized access control framework based on smart contracts with three parts: initialization, an access control protocol, and an inspection. Smart contracts are used in the proposed framework to store access control policies safely on the blockchain. The framework also penalizes users for attempting unauthorized access to the IoT resources. The smart contract was developed using Remix and deployed on the Ropsten Ethereum testnet. We analyze the performance of the smart contract-based access policies based on the gas consumption of blockchain transactions. Further, we analyze the system’s security, usability, scalability, and interoperability performance.

N-Accesses: A Blockchain-Based Access Control Framework for Secure IoT Data Management.

With the rapid advancement of network communication and big data technologies, the Internet of Things (IoT) has permeated every facet of our lives. Meanwhile, the interconnected IoT devices have generated a substantial volume of data, which possess both economic and strategic value. However, owing to the inherently open nature of IoT environments and the limited capabilities and the distributed deployment of IoT devices, traditional access control methods fall short in addressing the challenges of secure IoT data management. On the one hand, the single point of failure issue is inevitable for the centralized access control schemes. On the other hand, most decentralized access control schemes still face problems such as token underutilization, the insecure distribution of user permissions, and inefficiency.This paper introduces a blockchain-based access control framework to address these challenges. Specifically, the proposed framework enables data owners to host their data and achieves user-defined lightweight data management. Additionally, through the strategic amalgamation of smart contracts and hash-chains, our access control scheme can limit the number of times (i.e., n-times access) a user can access the IoT data before the deadline. This also means that users can utilize their tokens multiple times (predefined by the data owner) within the deadline, thereby improving token utilization while ensuring strict access control. Furthermore, by leveraging the intrinsic characteristics of blockchain, our framework allows data owners to gain capabilities for auditing the access records of their data and verifying them. To empirically validate the effectiveness of our proposed framework and approach, we conducted extensive simulations, and the experimental results demonstrated the feasibility and efficiency of our solution.

An Efficient Attribute-Based Encryption Scheme with Data Security Classification in the Multi-Cloud Environment

As an increasing number of people and corporations move their data to the cloud side, how to ensure efficient and secure access to data stored on the cloud side has become a key focus of current research. Attribute-Based Encryption (ABE) is largely recognized as the best access control method for safeguarding the cloud storage environment, and numerous solutions based on ABE have been developed successively. However, the majority of current research is conducted within a single cloud provider, and only the limited number of schemes for the multi-cloud environment also fail to support the data security classification on the cloud side. Therefore, we propose an efficient attribute-based encryption scheme with data security classification in the multi-cloud environment. In our scheme, the data owner’s data are divided into two security levels and stored in different cloud providers, which improves the security of outsourcing data. Moreover, based on Ciphertext-Policy Attribute-Based Encryption (CP-ABE), our scheme can not only provide a fine-grained access control for the data user, but also completely exploit the cloud side to facilitate outsourcing decryption to lighten the data user’s computing load. The security analysis showed that our scheme is effective against selective-attribute plaintext attack, as well as protects the privacy of the data. The experimental results also demonstrated that the computational overhead is obviously less than other existing schemes.

Security analysis of fog computing environment for ensuring the security and privacy of information

AbstractIn fog computing, the management, measurement, configuration, control, communication, and storage tasks are carried out collaboratively by one or more near‐user or end users. Fog computing is widely utilized in major application domains like centralized fog utilized in a shopping complex (UXFog), agriculture domain (FoAgro), health‐care domain (MediFog), vehicle parking system, and energy Lattices. The execution of fog computing at the system's edge provides the elevated quality of service (QoS), promotes area mindfulness, and minimal dormancy for the continuous and online streaming application areas. Fog networking is extremely concerned about wireless system security due to the prevalence of wireless communication in fog computing. Sniffer attacks, Jamming assaults, and several other intrusions are considered examples of security issues. While considering network storage issues, factors like interaction management, dynamic workload, and low dormancy are the most challenging aspects of designing the network model. Thus, privacy and security issues are crucial while designing the network model, accomplished through intrusion detection, access control and authentication methods. Therefore, the security analysis of fog computing based on authentication, access control and intrusion detection mechanisms are analyzed in this research to design a novel technique with enhanced security and privacy features for sharing and accessing information.

Dynamic access control method for SDP-based network environments

With online work environments and other distributed computing systems—such as cloud technologies or Internet of Things systems—becoming increasingly popular today due to the COVID-19 pandemic and general technological advances, the question of how to keep them secure has also become a pertinent concern. With this increased dependence on online systems for companies, cyberattacks have also been on the rise. To protect terminal devices, many companies have resorted to implementing a single boundary-defense model. This method has yielded positive results in securing the network from external threats, but it does not effectively protect network from internal security threats. With the vulnerabilities in the internal network security in mind, a dynamic access control method used with a zero-trust software-defined perimeter security model could be a viable solution. This study proposes a dynamic access control method using an engine with a new reward and penalty point-based system (RP Engine) and a dynamic task engine (DT Engine) for a zero-trust SDP security model.

Secure Big Data Storage on Multi-Cloud Servers with Enhanced Attribute-Based Access Control

Abstract: Data outsourcing is now subject to additional safety and privacy concerns as a result of the rise in cloud computing demand. Because data management was moved to words an unstable cloud during the outsourcing stage of the data, data permit control identified a key problem in the cloud repository. This analysis uses the Attribute-Based Access Control method to control access to the cloud storage to solve the issue. The data is reserved in the cloud and protected by strict security before the user may access it. This model takes into account specific properties of the cloud data stored in the database authentication process in order to store the information of registered collections alongside the user-committed data. Each of the clusters has a unique set of benefits, including usernames, group names, and registry message authorization codes. Prior to sending the data to the service provider, it should be encrypted to ensure its security. However, there may occasionally be problems with the supplier’s security measures. In this outcome, a variety of metrics are analyzed, such as the amount of time used for encryption, decryption, key generation, and time consumption. The numerous existing techniques, like Nth Truncated Ring Units and Cipher text. Constraints on online storage access may make policy attribute-based encryption impossible. The time of encryption is reduced by 20% and 36%, respectively, via NTRU and CP-ABE. The proposed technique decrypts data 10.64% faster than the current approach, which decrypts data 19% more slowly.

Automatic access control method of PLC stacker crane based on GA optimization algorithm

At present, car ownership is expanding, and parking facilities are insufficient. This problem has plagued people’s lives and hindered the development of cities. The stereo garage has become the main way to solve the parking problem. But the existing stereo garage is low in intelligence and low in vehicle entry efficiency. Therefore, in this study, a new vehicle entry strategy for the road stacking stereo garage is designed. GA algorithm is innovatively improved and applied to vehicle strategy optimization. By taking the dual objective function as the fitness function of the algorithm, the access strategy is optimized. Using MATLAB software to simulate and verify each access strategy and its improvement effect. This study provides guidance and data support for seeking the best vehicle access strategy. It has good practical application value for vehicle access in 3D garage.

A hybrid framework to enhance cloud security for storing and retrieving confidential data in clouds

<p>The building pieces for creating a secure cloud framework for data exchange with authenticated and authorized users are ECC and ABAC. So, the goal of this study is to improve access control and encryption-related methods in order to increase security. The elliptic curve is a key component of the comparative study of cloud encryption and access control techniques. This research project’s main goal is to provide a security architecture that combines authenticated access with attribute-based access control and better elliptic curve encryption. The second goal is to provide a better mapping strategy with reduced time and space complexity for elliptic curve encoding from plain text. To boost the performance of the standard ECC, a thorough algorithm focusing on designing an improved mapping mechanism for encoding plain text to elliptic curve points with excellent security has been included. The strength of the security should not be sacrificed in order to reduce security measures’ overhead costs. ABE is regarded as an effective way for protecting cloud data, according to study results. Because to the use of complex pairing processes, the same is difficult to use. As a result, a hybrid approach using ECC and ABAC performs better to handle the increasing processing capacity.</p>

Fully-Decoupled Radio Access Networks: A Resilient Uplink Base Stations Cooperative Reception Framework

To cope with the even more urgent spectrum and energy efficiency challenge for trillion-level terminal access and data uploading in the next generation mobile communication network (6G), in this paper, we investigate the uplink transmission in an original fully-decoupled radio access networks (FD-RAN) architecture. Specifically, we propose a resilient uplink base station cooperative reception framework in FD-RAN, which is a large-scale fading based two-tier signal combination approach for the uplink transmission, including the localized signal combination at the base station and centralized signal combination at the edge cloud, respectively. Then, we formulate a weighted sum-rate maximization problem for the uplink transmission optimization, and decompose it into two subproblems. A spectrum-efficiency maximized virtual service cluster selection (SEMVS) algorithm is designed by leveraging the channel statistical information for solving subproblem one, and a fractional programming based power control (FPPC) algorithm is introduced for the power optimization of subproblem two. Compared to the typical RAN architectures with corresponding access and power control methods, simulation results demonstrate the significant performance improvements of uplink FD-RAN with the proposed solution.

A Weighted GraphSAGE-Based Context-Aware Approach for Big Data Access Control.

Context information is the key element to realizing dynamic access control of big data. However, existing context-aware access control (CAAC) methods do not support automatic context awareness and cannot automatically model and reason about context relationships. To solve these problems, this article proposes a weighted GraphSAGE-based context-aware approach for big data access control. First, graph modeling is performed on the access record data set and transforms the access control context-awareness problem into a graph neural network (GNN) node learning problem. Then, a GNN model WGraphSAGE is proposed to achieve automatic context awareness and automatic generation of CAAC rules. Finally, weighted neighbor sampling and weighted aggregation algorithms are designed for the model to realize automatic modeling and reasoning of node relationships and relationship strengths simultaneously in the graph node learning process. The experiment results show that the proposed method has obvious advantages in context awareness and context relationship reasoning compared with similar GNN models. Meanwhile, it obtains better results in dynamic access control decisions than the existing CAAC models.

Fine-grained access control policy in blockchain-enabled edge computing

In the process of data sharing and interaction between untrusted intelligence edge devices, there are risks of misuse and tampering with the data. Hence, how to ensure data security and prevent unauthorized data access is the key problem to be solved in the cloud edge collaborative architecture. However, due to the heterogeneity of edge devices and the diversity of data sources, traditional access control methods cannot meet the requirements of the large-scale, distributed, dynamic and flexible expansion of edge intelligence applications. Therefore, this paper studies the fine-grained data access control method on the basis of smart contracts, and implements the attribute-based access control (ABAC) model through smart contracts. To improve the query efficiency of attributes and policies in the process of access request decision, an attribute management scheme is designed on the basis of the Bloom filter to achieve fast retrieval of attributes and policies. The decentralized fine-grained access control method is tested under the performance indicators such as retrieval delay, deployment delay, rule reduction rate and decision response time.

Designing a Robust Security Framework for Safeguarding Cloud Computing Environments in the Age of Cyber Threats

As online threats grow, it is very important to keep cloud computer settings safe. This paper suggests a complete security system that will keep cloud platforms and data safe from different threats. To make a multi-layered defense system, the framework combines a number of important parts, such as encryption methods, access control systems, and intruder detection systems. Strong encryption methods, like AES (Advanced Encryption Standard) and RSA (Rivest-Shamir-Adleman), are at the heart of the system. They protect the privacy and security of data. Strong key management techniques go along with these methods to keep encryption keys safe and stop people from getting in without permission. Based on the principle of least privilege, access control methods are very important for making sure that only the right people can use resources. Tough access rules are put in place with role-based access control (RBAC) and attribute-based access control (ABAC). In addition, the framework has an intrusion detection system (IDS) that constantly checks cloud settings for any strange activity. Machine learning techniques are used by the IDS to find and stop possible threats in real time. This security strategy covers all aspects of protecting cloud computing settings and adapts to the changing nature of cyber dangers. By using this framework, businesses can make their cloud systems safer and keep private data safe from threats and people who aren't supposed to see it.

Preference-Aware User Access Control Policy in Internet of Things.

There are multiple types of services in the Internet of Things, and existing access control methods do not consider situations wherein the same types of services have multiple access options. In order to ensure the QoS quality of user access and realize the reasonable utilization of Internet of Things network resources, it is necessary to consider the characteristics of different services to design applicable access control strategies. In this paper, a preference-aware user access control strategy in slices is proposed, which can increase the number of users in the system while balancing slice resource utilization. First, we establish the user QoS model and slice QoS index range according to the delay, rate and reliability requirements, and we select users with multiple access options. Secondly, a user preference matrix is established according to the user QoS requirements and the slice QoS index range. Finally, a preference matrix of the slice is built according to the optimization objective, and access control decisions are made for users through the resource utilization state of the slice and the preference matrix. The verification results show that the proposed strategy not only balances slice resource utilization but also increases the number of users who can access the system.

Data access control method of cloud network secure storage under Social Internet of Things environment

Data access control method of cloud network secure storage under Social Internet of Things environment