User Access Control Research Articles

Controlling user access with scripting to mitigate cyber-attacks

With the growing threats in the dynamic digital landscape, organizations are grappling with the difficult task of managing cyber-attacks by restricting user accessibility to most communication systems. This study aimed to develop a Linux script as a proactive response to the growing of cyber-attacks in organizational settings to prevent attacking vectors based on user negligence. The primary objective was to devise inventive solutions through script automation to restrict user access to the organizational network within predefined time frames, thereby mitigating potential cyber threats. The criteria used to define predefined time frames for user access, include the restriction of users on off duty times, The scripting seeks to address cyber-attacks targeted such as cross-site scripting (XSS) and SQL injection. To achieve the goal of this paper, the necessary steps and logic required to develop the scripts were taken. For instance, there are several suitable languages such as Bash, Python, or Perl, that can be used to write script. The paper selected Bash because it excels at scripting existing command-line tools and utilities, making it a great choice for automating tasks by using Vim text editor tool. The final scripts were run, some errors were identified, and modified as needed to ensure it worked correctly. This phase was necessary to improve the script's performance, readability, and maintainability by refining code, using efficient algorithms, by incorporating best practices. Finally, the various user inputs and scenarios were deployed to put the script into production for user access management. The adopted script metrics deployed such as Script Execution Time, Resources Utilization, Success Rate and Error Rate helped in evaluating the performance, efficiency, and effectiveness of the scripts. The implementation of the script achieved an executive time of 0.032 s, success rate was 1 and error rate was 0. The practical implementation in organizations can be scaled up or down depending on the organization's size and infrastructure. The compatibility of the developed Linux script with different operating systems, hardware platforms and network architectures will have no impact in adapting to various organizational environments. The script did not show any challenges, but real-world deployment may exhibit some potential challenges and limitations that may be associated with implementing the solution, such as resource constraints and legacy system compatibility.

An efficient ciphertext-policy weighted attribute-based encryption with collaborative access for cloud storage

The encryption of user data is crucial when employing cloud storage services to guarantee the security of these data stored on cloud servers. Attribute-based encryption (ABE) scheme is considered a powerful encryption technique that offers flexible and fine-grained access control capabilities. Further, the multi-user collaborative access ABE scheme additionally supports users to acquire access authorization through collaborative works. However, the existing multi-user collaborative access ABE schemes do not consider the different weights of collaboration users. Therefore, using these schemes for weighted multi-user collaborative access results in either redundant attributes or unsuccessful construction of the access control structure. For this, we proposes the special attribute policy (SAP) problem about weighted multi-user collaborative access, and presents an efficient ciphertext-policy weighted attribute-based encryption with collaborative access scheme (CP-WABE-CA), which can provide efficient collaborative access control for multiple users with different weights. In detail, this scheme utilizes a novel weighted access tree to prevent attribute repetition, thereby eliminating redundant attributes and addressing the issue of constructing access control structures. We prove our scheme is resistant against chosen plaintext attack. The experimental results demonstrate that our scheme has significant computational efficiency advantages compared to related works, without increasing storage or communication overhead. Therefore, the CP-WABE-CA scheme can provide an efficient flexible weighted collaborative access control mechanisms for cloud storage.

Optimization of gamified Learning Education Model based on XR + 5G technology

The new intelligent technology represented by 5G and XR has become the core driving force of the fourth industrial revolution, and the integrated application of the two in the field of education is also promoting the continuous transformation of teaching to gamification. Based on XR + 5G fusion technology, this paper proposes the optimization design of a gamified education model. Firstly, the problem of how to improve the network performance through D2D communication in a full-load 5G network is studied, and a D2D communication resource allocation framework based on cross-layer optimization design is proposed. In D2D user access control, a D2D user access criterion based on the distance between the CU user and D2D user receiver is designed according to the QoS requirement, maximum transmit power limit, and user channel information. XR simulation platform was designed based on a 5G network with optimized communication resource allocation. UMa and InH simulation scenarios were set according to XR business model working scenarios, and Wrap Around algorithm was used to model two circles of interference for users, ensuring the reliability of results while improving simulation efficiency. Finally, the platform channel was modeled strictly according to the channel modeling method in technical document 38.901, and the channel was calibrated with the channel provided by 3GPP. Based on the simulation platform, gamified education design is optimized. Including class platform and class platform gamification design, system demand analysis, and database design. In the gamification design, a relatively novel classroom interaction mode is introduced to increase students’ enthusiasm in class. In the demand analysis of the system, the main problems in class are listed, based on which the business and functional requirements of the gamification platform are determined. Experiments show that in the IID scenario, the proposed XR + 5G fusion technology can achieve 1.09 times the training speed and obtain 0.83 % learning accuracy gain compared with the individual learning algorithm. In the Non-IID scenario, the training speed of the proposed fusion technique is 1.03 times that of the individual learning algorithm, and there is a learning accuracy gain of 2.27 %.

Application of IoT audio technology based on sensor networks in English speaking teaching system

In the era of information technology, the exponential growth of data volume has compelled users to entrust their data to database service providers for efficient management. While traditional methods such as user authentication, security auditing, and access control have been implemented to safeguard data security across databases, cloud servers may face security challenges due to excessive internal administrator permissions. The audio technology of the Internet of Things (IoT) offers numerous advantages, including high bandwidth, short data transmission time, long transmission distance, and cost-effectiveness. It has found widespread applications in military, technological, industrial, and everyday life settings. With the advancements in modern information technology and the development and enhancement of wireless radio frequency technology in the IoT sector, IoT-based wireless audio interaction systems utilizing Wi-Fi have gradually become integrated into people's lives. These systems have enriched people's daily experiences and are increasingly popular among consumers. This paper, based on the theory of functional applied linguistics, combs the basic theoretical framework and the practical application prospect of functional Applied Linguistics of systemic language, especially emphasizes the important influence and application enlightenment of systemic functional linguistics on language teaching, and combines the "Recent Development Zone" The basic concepts of contemporary language and literature education, such as scaffolding, are summarized and analyzed. The paper establishes a comprehensive theoretical research framework for college spoken English teaching, and through the comprehensive theoretical analysis of communicative teaching methods and practical exploration of some problems that students may appear, it puts forward more effective and targeted specific solutions.

Enhancing security of cloud using static IP techniques

The user authentication and access control procedures for data stored on a cloud server encountered numerous security risks and concerns. Because critical company data should only be accessible by authorized workers, enhancing cloud security with static IP approaches is more beneficial. Even though the cloud providers maintain many security mechanisms, still the level of security should be raised by them due to lot of intruders who want to break their security mechanism. An encryption method is frequently used in most servers’ security mechanisms. In this security mechanism, data in the cloud server may be stolen and misused. Security mechanisms using static IP addresses are another method for data security in cloud security. This paper explains that the static IP address security mechanism is better and more goal-oriented than that of earlier security systems.

Models database of information technology for valuation of real estate

The goal of the research is to find and analyze ways to improve the results of real estate valuation based on a comparative approach. The chosen approach suggests the use of an information technology for the valuation of residential real estate, which is built on the basis of a database of models of decision support systems (DSS). The problem solved with the use of the discussed approach is to establish the degree of similarity between the object under consideration and its analogs by determining the value as an integral quality indicator based on the analysis of value-creating factors. This is followed by the construction of a generalized relationship between the value of this indicator and the prices of analogs. According to the logic of the comparative approach, it is assumed that the obtained relationship holds for the evaluated object as well and can be used in the calculation of its value.
 The formation of the database of models was based on the analysis of information technology processes, where details of functional aspects of process implementation, informational and logical connections between them, rights of access to information environment, and the implementation of processes by different types of users (their roles) were considered. The proposed database of models is built as a mathematical and logical basis of information technology that is applied as a computer tool for appraisers and aims to maximize formalization and efficiency improvement of process implementation based on expert evaluation methods. The construction of the database of models is based on methods of value estimation using multiple criteria, with consideration of their significance, analysis of hierarchies, ranking, Delphi, and user access control based on defined roles.

AI for Identity and Access Management (IAM) in the Cloud: Exploring the Potential of Artificial Intelligence to Improve User Authentication, Authorization, and Access Control within Cloud-Based Systems

This comprehensive study explores the integration and effectiveness of Artificial Intelligence (AI) in Identity and Access Management (IAM) within cloud environments. It primarily focuses on how AI can enhance user authentication, authorization, and access control, addressing the challenges and possibilities in cloud computing. The study adopts a mixed-methods approach, employing both quantitative and qualitative analyses. A survey involving 582 cybersecurity experts provides insights into the current state and potential of AI in IAM, while multiple regression analysis examines the impact of various factors on system effectiveness. Four hypotheses are explored: the impact of hardware and software configurations on system accuracy (H1), the influence of computational environments on reliability (H2), the role of demographic factors in user acceptance (H3), and the effect of technological enhancements on system performance and acceptance (H4). Findings indicate significant correlations between these factors and the effectiveness of AI in IAM. Notably, hardware configurations and security concerns influence system accuracy; computational environment variations affect system reliability; demographic factors impact user acceptance; and enhancements such as user feedback, advancements in AI technology, continuous learning algorithms, and system transparency improve performance and acceptance. These insights underscore the need for advanced hardware, standardized software, user-centric design, and continuous improvement in AI technologies for effective IAM in cloud environments. The study provides actionable recommendations for cloud service providers and developers, emphasizing the importance of involving users in development processes, ensuring transparency, and adopting adaptive algorithms. Future research directions include longitudinal studies on the impact of technological advancements and exploring demographic-specific responses to AI-integrated IAM solutions.

Network Attack Chain Security Model Construction Based On Attack Framework

All facets of society's governance, economics, and culture have been impacted by networking. Network attacks have become more common as a result of the digital revolution, which has also facilitated major changes in worldwide communication and accelerated the development of human society. An unauthorized attempt to access a network with the goal of committing theft or other forms of damage is what we call a network attack. This article focuses on building a chain security model utilising the block chain concept in order to address the issue of inaccurate assessments of forged malicious behavioural methods for identification. It uses the NIK-256 hashing algorithm to identify valid users utilising time-dependent verification. Passwords and recorded times are maintained in a combined chain database, which combines blockchain technology and the Trusted Platform Module (TPM), improving data security and privacy. After that, we schedule users using the Whale optimisation algorithm (WOA), which decreases difficulty, and then a smart contract is developed that grants authorised users access control based on their level of trust and permission. The proposed approach, known as Hyb_chain_TPM, implements countermeasures in accordance with the attack risk level and stores the attack graph in a combined chain database for future attack forecasting. Utilising diverse attack datasets, extensive tests are run to validate this system. Additionally, the outcomes of privacy protection and AI processes are assessed independently and contrasted using a variety of current techniques.

ASSESSMENT OF SERVICE QUALITY OF PASURUAN E-SAMBAT APPLICATION WITH E-GOVQUAL DIMENSION APPROACH

Public services are government mediators in providing services to the needs of the community. The development of technology makes it easier for state and regional apparatuses to provide public services through an application called E-Government. Similarly, the Pasuruan City Communication and Information Agency has tried to organize the E-Sambat application. This study aims to provide an understanding of the quality of E-Sambat services based on the E-GovQual dimension approach, the gap between E-Sambat performance and public expectations for the E-Sambat application, and knowing which items will be prioritized to be immediately improved in the E-Sambat application. To analyze the feasibility of the application using GAP and the Important Performance Analysis (IPA) method is used to analyze items that are prioritized for improvement. Respondents in this study were 445 respondents. Based on the results of the analysis conducted, the quality of E-Sambat application services is very feasible with a feasibility percentage value of 100%, application performance GAP and public expectations for the Ease of Use variable of 0.08, Trust variable of -0.04, Functionality of the Interaction Environment variable of 0.02, Reliability variable of -0.03, Content and Information Display variable of 0.01, and the Community Support variable of 0.00. The overall average gap is 0.01 which means that people are satisfied with the E-Sambat application service. There are six items that are prioritized for improvement, namely TR 1 (security of personal data of E-Sambat users), TR 6 (access control of E-Sambat users), RLB 1 (speed in downloading E-Sambat forms), CAI 7 (use of colors in the E-Sambat application), CAI 8 (graphics in the E-Sambat application), and CS 5 (User questions answered quickly).

AI for Identity and Access Management (IAM) in the Cloud: Exploring the Potential of Artificial Intelligence to Improve User Authentication, Authorization, and Access Control within Cloud-Based Systems

AI for Identity and Access Management (IAM) in the Cloud: Exploring the Potential of Artificial Intelligence to Improve User Authentication, Authorization, and Access Control within Cloud-Based Systems

A Unique Approach Towards Keystroke Dynamics Based Entry-point User Access Control

A Unique Approach Towards Keystroke Dynamics Based Entry-point User Access Control

A study of identity authentication using blockchain technology in a 5G multi-type network environment

The 5G technology, known for its large bandwidth, high speed, low latency, and multi-connection capabilities, significantly accelerates digital transformation in enterprises, especially in addressing factory automation challenges. It facilitates efficient machine-to-machine (M2M) and device-to-device (D2D) connectivity, ensuring rapid data transfer and seamless process convergence under 5G standards. Although 5G offers substantial communication and low latency benefits, its limited indoor coverage requires the deployment of decentralized antennas or small base stations. In contrast, Wi-Fi 6 seamlessly complements 5G, providing superior indoor mobile connectivity. This integration is crucial for businesses looking to accelerate digital transformation. To optimize 5G, the deployment of devices such as bypass switches, SDN switches, and MEC in the 5G Local Breakout network enables user access control and fast authentication. Real-world validation confirms the effectiveness of these measures, which are expected to lead to the future of 5G mobile networks.

A unique approach towards keystroke dynamics-based entry-point user access control

A unique approach towards keystroke dynamics-based entry-point user access control

A blockchain-based DAC distributed access control model

Access control systems allow organizations to control user access to their resources with high reliability and availability. Blockchain technology can help in this case. However, when it comes to storing access control data, especially the matrix that defines user rights to files (DAC model) may be too large to be handled by blockchain as is. Thus, a decentralized access control model that results in a small amount of data storage on the blockchain can be beneficial in terms of the reliability of blockchain networks while allowing it to scale by adding large numbers of users and files. We present access control DAC model which uses a Merkle tree to store data, minimizes the storage size on the blockchain. This solution can be used with a variety of file storage systems, regardless of the used file storage technology. The proposed approach suggests additionally caching some requests to increase scaling. The proposed model was tested on 500 objects in a distributed environment.

Securing the Future of Digital Marketing through Advanced Cybersecurity Approaches and Consumer Data Protection Privacy and Regulatory Compliance

The SecureDigitalGuard framework gets recognition for its all-encompassing strategy, which combines strict consumer data protection laws with state-of-the-art security safeguards with ease. This all-encompassing approach is designed to guarantee the longevity of digital marketing in the face of constantly changing cyberthreats. This cutting-edge system is based on three key strategies: the Behavioural Threat Detection (BTD) algorithm, the Adaptive Access Control (AAC) algorithm, and the Homomorphic Privacy Guard (HPG) programme. The vital task of dynamically controlling user access levels in response to continuing risk evaluations is taken on by the AAC algorithm. This dynamic control technique improves the framework's capacity to adjust to constantly shifting security circumstances. However, the BTD algorithm is proactive in spotting abnormalities in user behaviour, allowing for quick reactions to any dangers. The SecureDigitalGuard architecture gains an additional degree of protection from this preventive method. In addition, the HPG programme is responsible for doing analytics while maintaining user privacy. This careful approach shows a dedication to finding a fine balance between user protection and data analysis, making sure the framework complies with the strictest privacy regulations. Test results provide empirical evidence that SecureDigitalGuard is effective and that it can keep up with the dynamic and often changing nature of cyber threats. As a result, the architecture makes traditional cybersecurity techniques outdated. In an increasingly complex and dynamic cybersecurity world, SecureDigitalGuard provides a strong solution for protecting digital marketing through the seamless integration of state-of-the-art technology and strict adherence to privacy regulations.

A Blockchain-Based Secure Searching Strategy for Metadata in Mobile Edge Computing

With intelligent devices’ prevalence, mobile edge computing technology can effectively process the massive data in the Internet of Things (IoT). The metadata produced in mobile edge computing plays a role in colossal data management. However, it also includes lots of user privacy information. Traditional privacy protection solutions sacrifice the metadata’s availability or are incompatible with the distributed environment. To overcome this dilemma, we propose a blockchain-based secure searching strategy for metadata (BSSMeta) in mobile edge computing. By leveraging a lightweight proxy re-encryption scheme and a decentralized key generation method on the blockchain, BSSMeta keeps the security of the metadata searching tasks. Meanwhile, a master-slave smart contract method and a buffer uploading strategy are proposed for the efficiency of the searching and uploading processes. As a byproduct, BSSMeta also supports searching metadata in a multi-user environment and gives users access control to metadata. Finally, we provide a security analysis of BSSMeta and implement a prototype on the Hyperledger Fabric platform. The results of experiments on various workloads show that BSSMeta is feasible and flexible in security and efficiency.

Data Security Issues and Countermeasure Suggestions for Financial Big data: A Literature Review

Financial Big Data is a contentious topic that needs to be addressed because it is having an increasingly negative impact on people's everyday lives, work habits, and thought patterns. The leakage of financial big data is just one of the issues that financial big data is now dealing with. As a result, the study focus of this work is on the data security problems and solutions related to financial big data. This paper summarizes four main categories of data security issues related to financial big data: attacks on financial big data, data leaks related to financial big data, issues with the reliability of financial big data, and issues with access control related to financial big data. Based on these four problem categories, it searches the literature and organizes the suggested solutions as follows: pay attention to the development of financial data security systems in a big data environment, strengthen education and training, increase the da-ta security awareness of various roles, optimize the processing of big data, and strengthen the storage security of big data by strict user access control. This paper's thought and research also reveal that while financial big data does provide data security issues, it also serves as the primary means of addressing the issue itself. Less research has been done on using financial big data as a countermeasure in and of itself. In the future, we should focus on financial big data itself and explore ways to use financial big data as a countermeasure to data security problems.

Secondary User Access Control in Cognitive Radio Networks: Concept, Design, and Analysis

Cognitive radio (CR), an important part of nextgeneration wireless communications networks, has been extensively studied to improve the spectrum utilization. The spectrum sensing and access functions are especially crucial for ensuring the secure and efficient spectrum sharing needs of CR networks. In this article, the secondary user access control (SUAC) based spectrum access technique is investigated to improve spectrum efficiency and network safety, by which a jamming signal is carefully designed to break down unauthorized secondary users (UA-SUs) sensing result and keep reliable sensing result from authorized secondary users (A-SUs). First, SUAC techniques are described, and a jamming cancellation method based on an oblique projection approach is proposed to guarantee the sensing result of authorized secondary users. Second, a prioritized SUAC approach is examined to ensure A-SUs with distinct spectrum access levels. Third, quadratic programming in massive multipleinput multiple-output based SUAC is presented to effectively design a jamming signal that combines minimizing jammer's influences on A-SUs and maximizing influences on UA-SUs. Finally, some open research areas and challenges in SUAC are discussed.

MQTT and blockchain sharding: An approach to user-controlled data access with improved security and efficiency

The rapid growth of the Internet of Things (IoT) has raised security concerns, including MQTT protocol-based applications that lack built-in security features and rely on resource-intensive Transport Layer Security (TLS) protocols. This paper presents an approach that utilizes blockchain technology to enhance the security of MQTT communication while maintaining efficiency. This approach involves using blockchain sharding, which enables higher scalability, improved performance, and reduced computational overhead compared to traditional blockchain approaches, making it well-suited for resource-constrained IoT environments. This approach leverages Ethereum blockchain's smart contract mechanism to ensure trust, accountability, and user privacy. Specifically, we introduce a shard-based consensus mechanism that enables improved security while minimizing computational overhead. We also provide a user-controlled and secured algorithm using Proof-of-Access implementation to decentralize user access control to data stored in the blockchain network. The proposed approach is analyzed for usability, including metrics such as bandwidth consumption, CPU usage, memory usage, delay, access time, storage time, and jitter, which are essential for IoT application requirements. The analysis demonstrated that the approach reduces resource consumption, and the proposed system outperforms TLS and existing blockchain approaches in these metrics, regardless of the choice of the MQTT broker. Additionally, thoroughly addressing future research directions, including issues and challenges, ensures careful consideration of potential advancements in this domain.

SUSIC: A Secure User Access Control Mechanism for SDN-Enabled IIoT and Cyber–Physical Systems

The integration of thriving Information and Communications Technology (ICT) and Cyber Physical Systems (CPS) has spawned several innovative applications such as remote healthcare, smart and intelligent transportation, smart logistics, smart grids, public safety etc. An emerging Software Defined Networks (SDN) technology further enabled to optimize the communication among industrial IoT (IIoT) and CPS entities. Nonetheless, the communication on public channel among different IIoT entities in an SDN-enabled environment may be exposed to various security threats due to wireless and insecure communication channels. To counter these security challenges in the way of wider CPS or IIoT adoption, we propose a novel three-factor authenticated key exchange mechanism (SUSIC) for SDN-enabled IIoT ecosystem. The SUSIC enables a registered user to access real-time data from physical IIoT environment directly after having mutual authentication performed through SDN-enabled controller node. The scheme is proved to be secure under rigorous formal and informal security analysis. Moreover, the simulation results and performance evaluation signifies towards achieving better trade-off between security functionalities and computational overheads comparatively.