Access Control Techniques Research Articles

A Novel Security Model for Password Encryption Using Aadhaar and Amicable Number

In this day and age, data hacking has become a major source of fear. In order to avoid any further theft of data, we must stop this criminal hacking. Backups, encryption, access control, and other techniques are just a few that may be used to ensure data integrity. We did not combine the existing approaches when we announced our encryption process. The secret to encrypting user passwords is to utilize a mathematical calculation equation that is well-defined and a number conversion mechanism. Users must provide their password and Aadhaar number in order to register. Encrypted password has been recorded in the database. Every industry uses encryption to secure data, and there are many potential applications for it in the future.

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>

A Comprehensive Review of Security Measures in Database Systems: Assessing Authentication, Access Control, and Beyond

This paper presents a comprehensive review of security measures in database systems, focusing on authentication, access control, encryption, auditing, intrusion detection, and privacy-enhancing techniques. It aims to provide valuable insights into the latest advancements and best practices in securing databases. The review examines the challenges, vulnerabilities, and mitigation strategies associated with database security. It explores various authentication methods, access control models, encryption techniques, auditing and monitoring approaches, intrusion detection systems, and data leakage prevention mechanisms. The paper also discusses the impact of emerging trends such as cloud computing, big data, and the Internet of Things on database security. By synthesizing existing research, this review aims to contribute to the advancement of database security and assist organizations in protecting their sensitive data.

An efficient chain code for access control in hyper ledger fabric healthcare system

The emergence of eHealth has been instrumental in enhancing healthcare systems, offering improved health services to diverse patients with the aid of cutting-edge technologies. The safe and effective collection, transmission, and accessibility of electronic health records (EHRs) using modern information and communication technologies (ICTs) is essential for realizing the goals of eHealth. However, the use of EHRs by healthcare practitioners creates the risk of data breaches and jeopardizes patient confidentiality. Fortunately, smart contracts and blockchain technology offer effective EHR access control techniques that can enable secure client identification, authentication, and authorization, enhancing the security of EHRs.So, this paper brings effective Blockchain-based solutions using Hyperledger fabric for providing privacy to EHRs. An effective deployment architecture and chain code were generated for design and access control. In this case, the utilization of Hyperledger Fabric as the Blockchain technology introduces a new consensus mechanism, enabling efficient scalability and safeguarding anonymity. By employing Hyperledger Fabric for framework development, the system achieves its objectives. Experimental results are carried out for analyzing the system performance and also computational tests.

Systematic Literature Review on Security Access Control Policies and Techniques Based on Privacy Requirements in a BYOD Environment: State of the Art and Future Directions

The number of devices connected within organisational networks through ”Bring Your Own Device” (BYOD) initiatives has steadily increased. BYOD security risks have resulted in significant privacy and security issues impacting organisational security. Many researchers have reviewed security and privacy issues in BYOD policies. However, not all of them have fully investigated security and privacy requirements. In addition to describing a system’s capabilities and functions, these requirements also reflect the system’s ability to eliminate various threats. This paper aims to conduct a comprehensive review of privacy and security criteria in BYOD security policies, as well as the various technical policy methods used to mitigate these threats, to identify future research opportunities. This study reviews existing research and highlights the following points: (1) classification of privacy and security requirements in the context of BYOD policies; (2) comprehensive analyses of proposed state-of-the-art security policy technologies based on three layers of security BYOD policies, followed by analyses of these technologies in terms of the privacy requirements they satisfy; (3) technological trends; (4) measures employed to assess the efficacy of techniques to enhance privacy and security; and (5) future research in the area of BYOD security and privacy.

Методика подвійної автентифікації для RFID систем управління доступом з підвищеним рівнем захисту

Currently, there are no uniform international standards for devices and systems that use radio frequency identification technology. Using tag alone as an identifier imposes certain restrictions on the level of protection of access control systems, since the unique tag identifier can be easily copied, so two-step authentication is required. The second level of protection can be a digital password entered via the keyboard. The work presents dual authentication technique for access control to the premises. Increasing the level of protection of radio frequency identification systems is achieved by the additional use of a digital password encrypted using a symmetric block encryption algorithm and recorded on the tag. This removes any restrictions on the number of registered users in the system, because passwords and IDs are stored on tags. The laboratory model of the device is based on the NodeMCU-32S Opensource platform with an RFID module that allows connection to most fog and cloud services of the Internet of things. The development is based on the ESP32 controller, which supports the necessary set of commands and hardware for implementing the methodology, in particular, wireless standards and communication protocols, hardware-accelerated encryption. The Cayenne service from MyDevices was chosen as the cloud platform, which made it possible to configure the device using the publish-subscribe messaging protocol and develop a graphical user interface. A log on the Cayenne platform is used to keep track of users, a character display is used to display the current status and settings of the device, and a serial interface is used to debug work algorithms. The software is implemented using the Arduino C programming language.

Enhanced Adaptable and Distributed Access Control Decision Making Model Based on Machine Learning for Policy Conflict Resolution in BYOD Environment

Organisations are adopting new IT strategies such as “Bring Your Own Device” (BYOD) and remote working. These trends are highly beneficial both for enterprise owners and employees in terms of increased productivity and reduced costs. However, security issues such as unauthorised access as well as privacy concerns pose significant obstacles. These can be overcome by adopting access control techniques and a dynamic security and privacy policy that governs these issues where they arise. Policy decision points in traditional access control systems, such as role-based access control (RBAC), attribute-based access control (ABAC), or relationship-based access control (ReBAC), may be limited because the status of access control can vary in response to minor changes in user and resource properties. As a result, system administrators rely on a solution for constructing complex rules with many conditions and permissions for decision control. This results in access control issues, including policy conflicts, decision-making bottlenecks, delayed access response times and mediocre performance. This paper proposes a policy decision-making and access control-based supervised learning algorithm. The algorithm enhances policy decision points (PDPs). This is achieved by transforming the PDP’s problem into a binary classification for security access control that either grants or denies access requests. Also, a vector decision classifier based on the supervised machine learning algorithm is developed to generate an accurate, effective, distributed and dynamic policy decision point (PDP). Performance was evaluated using the Kaggle-Amazon access control policy dataset, which compared the effectiveness of the proposed mechanism to previous research benchmarks in terms of performance, time and flexibility. The proposed solution obtains a high level of privacy for access control policies because the PDP does not communicate directly with the policy administration point (PAP). In conclusion, PDP-based ML generates accurate decisions and can simultaneously fulfill multiple massive policies and huge access requests with 95% Accuracy in a short response time of around 0.15 s without policy conflicts. Access control security is improved by making it dynamic, adaptable, flexible and distributed.

Medium Access Control Techniques for Massive Machine-Type Communications in Cellular IoT Networks

A key component of the Internet of things (IoT) ecosystem is wide-area network connectivity, for which cellular network technologies are a promising option through their support of massive machine-type communications (mMTC). However, numerous devices transmitting sporadically small data packets in a highly synchronized way can generate overload on the radio access network. This situation leads to a shortage of resources, especially those associated with the random access procedure for contention, control, and data transmission, causing preamble collision, control message blocking, and data collision. As a result, mMTC traffic can jeopardize the provisioning of quality of service (QoS) to end-devices, decrease the network efficiency, and increase access latency and device energy consumption. This paper proposes medium access control (MAC) techniques for addressing problems related to the support of mMTC in cellularnetworks. First, a solution for allocating control resources with QoS provisioning and access differentiation is provided, including a resource management model, a scheduling algorithm, and a message prioritization policy. Second, a mechanism for reducing data collisions is also proposed. This solution comprises a protocol in which every device with scheduled retransmission uses a probabilistic policy to decide whether to retransmit, a novel method at the device to estimate the number of nodes trying random access, and two different retransmission policies employing this estimation. Results show that the proposals support QoS, decrease access latency, decrease the device energy consumption, and increase resource utilization under massive random access.

An Improved Quality Enhancement Fingerprint Analysis

The use of fingerprint authentication as a biometric technique for secure authentication and access control has gained significant traction in recent years. This article presents an overview of the technology used for fingerprint identification, its history, as well as the fundamental components that make up a fingerprint recognition system. We also go through the many approaches to fingerprint identification techniques and algorithms, such as the minutiae-based approach, the ridge feature-based approach, and the pattern recognition-based approach. All of these are utilized in the process of authenticating fingerprints. In addition, we emphasize the limitations of fingerprint authentication as well as the security risks that are linked with it, as well as alternative methods to overcome these constraints.

Secure multi-factor access control mechanism for pairing blockchains

Digitalization has made it easier for centric systems to transition from single-factor to two-factor authentication. However, several access control practices struggle to authenticate users correctly due to their weak and outdated authorization systems. Moreover, the majority of cloud-centric models suffer from security and single-point-of-failure issues. Consequently, several systems have migrated their access control services to the blockchain. A good illustration is using two-factor authentication techniques to increase transaction security in Bitcoin systems. However, with this holistic trend of 2FAs, multi-factor authentication has yet to see this trend. In this regard, the study proposes an access control technique that combines multiple factors of knowledge, inherent, and possession to authenticate users to the blockchain. The multiple factors derive a time-based access code for users to generate private keys. The efficiency of the proposed method is tested with a Py-Eth-pairing library to determine the computation cost and transmission overhead. Furthermore, we use the EIP (Ethereum Improvement Proposals) library to assess the gas cost and determine the throughput. Our findings show the suggested approach to achieving the lowest operational cost, making it scalable on the blockchain while demonstrating its practicability through the model framework.

Access Control Design Practice and Solutions in Cloud-Native Architecture: A Systematic Mapping Study.

Protecting the resources of a cloud-native application is essential to meet an organization's security goals. Cloud-native applications manage thousands of user requests, and an organization must employ a proper access control mechanism. However, unfortunately, developers sometimes grumble when designing and enforcing access decisions for a gigantic scalable application. It is sometimes complicated to choose the potential access control model for the system. Cloud-native software architecture has become an integral part of the industry to manage and maintain customer needs. A microservice is a combination of small independent services that might have hundreds of parts, where the developers must protect the individual services. An efficient access control model can defend the respective services and consistency. This study intends to comprehensively analyze the current access control mechanism and techniques utilized in cloud-native architecture. For this, we present a systematic mapping study that extracts current approaches, categorizes access control patterns, and provides developers guidance to meet security principles. In addition, we have gathered 234 essential articles, of which 29 have been chosen as primary studies. Our comprehensive analysis will guide practitioners to identify proper access control mechanisms applicable to ensuring security goals in cloud-native architectures.

Modelling of ML-Enablers in 5G Radio Access Network-Conceptual Proposal of Computational Framework

The fifth generation (5G) of mobile networks connects people, things, data, applications, transport systems, and cities in smart networked communication environments. With the growth in the amount of generated data, the number of wirelessly connected machines, traffic types, and associated requirements, ensuring high-quality mobile connectivity becomes incredibly difficult for technology suppliers. Mobile operators and network vendors enrolling in 5G face far more rapid demands than any technology before, and at the same time need to ensure efficiency and reliability in the network operations. In fact, intelligent forecasting and decision-making strategies are several of the centerpieces of current artificial intelligence research in various domains. Due to its strong fitting ability, machine learning is seen to have great potential to be employed to solve telecommunication networks’ optimization problems that range from the design of hardware elements to network self-optimization. This paper addresses the question of how to apply artificial intelligence to 5G radio access control and feed ML techniques with radio characteristic-based automatic data collection to achieve ML-based evaluation of 5G performance. The proposed methodology endorses ML tools for the 5G portfolio scenarios requirements assessment and integrates into the mature methods for network performance optimization: self-organizing networks (SON) and minimization of drive tests (MDT). In this context, the proposed treatment guides future network deployments and implementations adopted on a 3GPP standard basis.

Ether-IoT: A Realtime Lightweight and Scalable Blockchain-Enabled Cache Algorithm for IoT Access Control

Several unique characteristics of Internet of Things (IoT) devices, such as distributed deployment and limited storage, make it challenging for standard centralized access control systems to enable access control in today’s large-scale IoT ecosystem. To solve these challenges, this study presents an IoT access control system called Ether-IoT based on the Ethereum Blockchain (BC) infrastructure with Attribute-Based Access Control (ABAC). Access Contract (AC), Cache Contract (CC), Device Contract (DC), and Policy Contract (PC) are the four central smart contracts (SCs) that are included in the proposed system. CC offers a way to save user characteristics in a local cache system to avoid delays during transactions between BC and IoT devices. AC is the fundamental program users typically need to run to build an access control technique. DC offers a means for storing the resource data created by devices and a method for querying that data. PC offers administrative settings to handle ABAC policies on users’ behalf. Ether-IoT, combined with ABAC and the BC, enables IoT access control management that is decentralized, fine-grained and dynamically scalable. This research gives a real-world case study to illustrate the suggested framework’s implementation. In the end, a simulation experiment is performed to evaluate the system’s performance. To ensure data integrity in dispersed systems, the results show that Ether-IoT can sustain high throughput in contexts with a large number of requests.

Steganographic secret sharing via AI-generated photorealistic images

Steganographic secret sharing is an access control technique that transforms a secret message into multiple shares in a steganographic sense. Each share is in a human-readable format in order to dispel suspicion from a malicious party during transmission and storage. Such a human-readable format can also serve to facilitate data management. The secret can be reconstructed only when a sufficient number of authorized shareholders collaborate. In this study, we use neural networks to encode secret shares into photorealistic image shares. This approach is conceptually related to coverless image steganography in which the data are transformed directly into an image rather than concealed into a cover image. We further implement an authentication mechanism to verify the integrity of the image shares presented in the decoding phase. All coverless image steganography schemes can be used to achieve steganographic secret sharing, but our detection mechanism can further improve the robustness of these schemes. Experimental results confirm the robustness of the proposed scheme against various steganalysis and tampering attacks.

Privacy Protected Preservation of Electric Vehicles’ Data in Cloud Computing Using Secure Data Access Control

Cloud computing provides a ubiquitous data storage and access mechanism for organizations, industries, and smart grids to facilitate their operations. However, the concern in cloud storage systems is to secure data access control toward authentication for sensitive data, such as the electric vehicles (EVs) requesting information for attending a charging service. Consequently, denying an authentic user’s request will result in delaying the requested service, thereby leading to service inefficiency. The role-based access control (RBAC) plays a crucial role in securing and authenticating such time-sensitive data. The design mechanism of roles is based on skills, authority, and responsibilities for organizations. For EVs, the roles are based on the type of membership, such as permanent, occasional, or one-time. In this paper, we propose a new RBAC access control and privacy-preserving information access method toward the coarse-grained measure control and privacy protection in the cloud storage system for EVs. The data can be encrypted and decrypted based on the types of users who possess appropriate access permission toward authorized and unauthorized users according to their roles specified by role-based access control policies. The proposed approach has been simulated with various role-based scenarios, and the efficiency was evaluated against state-of-the-art role-based access-control techniques.

Enhanced cipher text-policy attribute-based encryption and serialization on media cloud data

PurposeThere are various system techniques or models which are used for access control by performing cryptographic operations and characterizing to provide an efficient cloud and in Internet of Things (IoT) access control. Particularly in cloud computing environment, there is a large-scale distribution of these traditional symmetric cryptographic techniques. These symmetric cryptographic techniques use the same key for encryption and decryption processes. However, during the execution of these phases, they are under the problems of key distribution and management. The purpose of this study is to provide efficient key management and key distribution in cloud computing environment.Design/methodology/approachThis paper uses the Cipher text-Policy Attribute-Based Encryption (CP-ABE) technique with proper access control policy which is used to provide the data owner’s control and share the data through encryption process in Cloud and IoT environment. The data are shared with the the help of cloud storage, even in presence of authorized users. The main method used in this research is Enhanced CP-ABE Serialization (E-CP-ABES) approach.FindingsThe results are measured by means of encryption, completion and decryption time that showed better results when compared with the existing CP-ABE technique. The comparative analysis has showed that the proposed E-CP-ABES has obtained better results of 2373 ms for completion time for 256 key lengths, whereas the existing CP-ABE has obtained 3129 ms of completion time. In addition to this, the existing Advanced Encryption Standard (AES) scheme showed 3449 ms of completion time.Originality/valueThe proposed research work uses an E-CP-ABES access control technique that verifies the hidden attributes having a very sensitive dataset constraint and provides solution to the key management problem and access control mechanism existing in IOT and cloud computing environment. The novelty of the research is that the proposed E-CP-ABES incorporates extensible, partially hidden constraint policy by using a process known as serialization procedure and it serializes to a byte stream. Redundant residue number system is considered to remove errors that occur during the processing of bits or data obtained from the serialization. The data stream is recovered using the Deserialization process.

Context-Based, Predictive Access Control to Electronic Health Records

Effective access control techniques are in demand, as electronically assisted healthcare services require the patient’s sensitive health records. In emergency situations, where the patient’s well-being is jeopardized, different healthcare actors associated with emergency cases should be granted permission to access Electronic Health Records (EHRs) of patients. The research objective of our study is to develop machine learning techniques based on patients’ time sequential health metrics and integrate them with an Attribute Based Access Control (ABAC) mechanism. We propose an ABAC mechanism that can yield access to sensitive EHRs systems by applying prognostic context handlers where contextual information, is used to identify emergency conditions and permit access to medical records. Specifically, we use patients’ recent health history to predict the health metrics for the next two hours by leveraging Long Short Term Memory (LSTM) Neural Networks (NNs). These predicted health metrics values are evaluated by our personalized fuzzy context handlers, to predict the criticality of patients’ status. The developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism with personalized context handlers proved to be a robust tool to enhance the performance of the access control mechanism to modern EHRs System.

Trust-Based Smart Contract for Automated Agent to Agent Communication.

Blockchain technology is now regarded as one of the most interesting and possibly innovative technologies. It enables information to be stored and exchanged securely and transparently without the need for a centralized authority to regulate it. Some of the primary benefits of this technology are the atomicity of the stored data. Given its features, this technology has the potential to provide answers to challenges encountered in a very sensitive sector, namely, Internet of Vehicles (IoV). In IoV, vehicles and service providers autonomously capture and produce data without human intervention. This exchanged data must meet certain criteria such as decentralization, automation, security, and stakeholder trust management. To overcome these challenges, the integration of blockchain technology and multi-agent systems is a key solution. Based on smart contracts, the proposed solution consists of exploiting role-based access control (RBAC) and attribute-based access control (ABAC) techniques. This solution removes the central authority (CA) to reduce maintenance costs and eliminate legacy threats from centralized systems. The results, obtained from consumption costs, show that the developed platform is characterized by security, availability, and privacy.

Implementing efficient attribute encryption in IoV under cloud environments

CP-ABE is a flexible cryptographic algorithm that enables efficient implementation of access control techniques in cloud architectures. However, when CP-ABE is applied to the IoV environment, the weak performance of IoV individuals will inevitably reduce the efficiency of the overall cryptosystem. In addition, various contingencies in IoV require CP-ABE to be able to dynamically respond to various access requests, and generating only a single ciphertext cannot satisfy various additional access requests. In this paper, we propose an encryption algorithm VM-CP-ABE for IoV in cloud environment, which has the features of offline encryption and outsourced decryption. The offline encryption process utilizes the large amount of offline time of individuals in the vehicular network to generate the initial ciphertext segments, while executing its secret sharing process for each offline phase of the ciphertext segments, thus completing the initial combination of ciphertext parameters. The outsourced decryption can generate transformation keys, thus stripping the most complex pairing operations in the decryption process from the weak performing IoV individuals and transferring this part of operations to the more powerful outsourced individuals. In addition, VM-CP-ABE can generate special hierarchical ciphertexts that will have a smaller ciphertext space. And it can avoid the problem of space efficiency due to the high volume of access control policy transfer. We show the static security of all mechanisms of VM-CP-ABE and conclude with a detailed efficiency analysis. VM-CP-ABE is more time- and space-efficient than traditional attribute encryption for extensive sets of IoV attributes in cloud environments.

Who’s Controlling My Device? Multi-User Multi-Device-Aware Access Control System for Shared Smart Home Environment

Multiple users have access to multiple devices in a smart home system – typically through a dedicated app installed on a mobile device. Traditional access control mechanisms consider one unique, trusted user that controls access to the devices. However, multi-user multi-device smart home settings pose fundamentally different challenges to traditional single-user systems. For instance, in a multi-user environment, users have conflicting, complex, and dynamically-changing demands on multiple devices that cannot be handled by traditional access control techniques. Moreover, smart devices from different platforms/vendors can share the same home environment, making existing access control obsolete for smart home systems. To address these challenges, in this paper, we introduce Kratos+ , a novel multi-user and multi-device-aware access control mechanism that allows smart home users to flexibly specify their access control demands. Kratos+ has four main components: user interaction module, backend server, policy manager, and policy execution module. Users can easily specify their desired access control settings using the interaction module that are translated into access control policies in the back-end server. The policy manager analyzes these policies, initiates automated negotiation between users to resolve conflicting demands, and generates final policies to enforce in smart home systems. We implemented Kratos+ as a platform-independent solution and evaluated its performance on real smart home deployments featuring multi-user scenarios with a rich set of configurations (337 different policies including 231 demand conflicts and 69 restriction policies). These configurations also included five different threats associated with access control mechanisms. Our extensive evaluations show that Kratos+ is very effective in resolving conflicting access control demands with minimal overhead. We also performed an extensive user study with 72 smart home users to better understand the user’s needs before designing the system and a usability study to evaluate the efficacy of Kratos+ in a real-life smart home environment.