Access Control Techniques Research Articles

Development of a Smart Lock System using QR Code Technology

A smart lock system refers to a modern security solution that enables users to remotely control access to their homes or businesses using a smart device such as smartphone, tablet, or computer. This paper presents the development of a smart lock system using Quick Response (QR) code technology to address the problem of insecurity, inconvenience, and inflexibility in access control. The proposed system eliminates the need for physical keys or complex authentication and verification methods. The system integrates an ESP8266 microcontroller, barcode scanner, 16x2 liquid-crystal display (LCD), solenoid lock, relay, and a 12V power supply. The system allows authorised users to generate unique QR codes representing their access credentials through a user-friendly interface. These QR codes are scanned by the system, which processes the codes, verifies access permissions via a central server and provides real-time feedback through the LCD. Upon successful verification, the system triggers a relay to control the solenoid lock, to grant or deny access. The implementation and testing of the smart lock system demonstrated successful operation. The performance indices include authentication speed, system reliability, accuracy and response time, which were evaluated and found to be satisfactory. The obtained results showed that the proposed system outperformed traditional methods such as keys, and fingerprint authentication, with an access speed of 2.00 seconds, which is significantly faster than the alternatives. Comparative analysis with existing access control techniques demonstrated the developed system's enhanced security features and user-friendly operation, making it applicable for residential, commercial, and industrial use. Additionally, the system's scalability and adaptability allow it to be customised for various environments, offering a versatile solution to diverse security challenges. This work contributes to the field of security technology by providing an efficient and scalable smart lock system with novel algorithms, which enhances the convenience, robustness of access control and seamless user experience.

Study of Access Control Techniques on the Blockchain-enabled Secure Data Sharing Scheme in Edge Computing

Background: The pervasive adoption of edge computing is reshaping real-time big data analysis, smart city management, intelligent transportation, and various other domains. Its appeal lies in its distributed nature, decentralization, low latency, mobile support, and spatial awareness. However, this ubiquity exposes data to security threats, jeopardizing privacy and integrity. Consequently, access control assumes paramount importance in securing data sharing within edge computing and blockchain technologies. Methods: This research addresses this critical issue by conducting a comprehensive study on access control techniques within the context of edge computing and blockchain for secure data sharing. Our methodology commences with an exhaustive review of relevant articles, aiming to identify and expound upon gaps in existing research. Subsequently, we perform a meticulous analysis of access control methods, mechanisms, and performance metrics, seeking to establish a holistic understanding of the landscape. Results: The culmination of this research effort is a multifaceted contribution. We distill insights from a diverse range of access control schemes, shedding light on their nuances and effectiveness. Our analysis extends to evaluating the performance metrics vital for ensuring robust access control. Through this research, we also pinpoint critical research gaps within traditional access control methods, creating a foundation for innovative approaches to address the evolving challenges within edge computing and blockchain environments. Conclusion: In conclusion, this research venture paves the way for secure data sharing in edge computing and blockchain by offering a thorough examination of access control. The findings from this study are anticipated to guide future developments in access control techniques and facilitate the evolution of secure, privacy-conscious, and efficient data sharing practices in the dynamic landscape of digital technology.

PDAC-SL: A PUF-enabled drone access control technique for smart logistics

The conventional logistics’ paradigm is being replaced with smarter ways of supply chain management to readily serve the customers with quick modes of delivery in affordable operational costs. The weak infrastructure in rural terrain and congested roads in urban cities act as a big impediment in the successful accomplishment of last mile delivery down the lane across the complete chain of logistics. The traditional logistics has been evolved and improved in many respects, the last mile delivery is still plagued by security and privacy risks in logistics. The use of drones for package deliveries may offer promising gains in terms of efficiency. Nonetheless, drones undergo security and privacy risks besides physical threats for being deployed in public places communicating on open channels. Thus, more efforts are needed to secure the communication of inducted drones in delivery assignments. We propose a novel PUF-enabled drone access control mechanism PDAC-SL for smart logistics. By the careful employment of symmetric crypto-primitives, the contributed protocol not only supports low end devices but stands resistant to physical drone and other known threats besides preserving anonymity and untraceability features. The RoR model-based formal security analysis and performance analysis demonstrate distinct security properties and applicability of the PDAC-SL.

E-SAFE: A secure and efficient access control scheme with attribute convergence and user revocation in fog enhanced IoT for E-Health

The growth of IoT led to a surge in connected devices and data production in the medical field. Therefore, to meet the rising demand for modern healthcare services, Fog and Cloud services come as a rescue for IoT-based equipment. As data travels through several levels, providing security to such data is challenging. The CP-ABE cryptographic approach allows for efficient access control. However, none of the known cryptographic CP-ABE approaches that provide granular access control offers the following features: attribute convergence, privileged access, user revocation, and outsourcing capabilities altogether. Thus, we present e-SAFE, a CP-ABE approach which addresses all these issues. In addition, in e-SAFE, the data users with resource-constrained medical gadgets must save just a constant and small-size decryption key on their gadgets. According to our assessment of security and performance, e-SAFE is found to be a secure and efficient access control technique for IoT gadgets.

Designing efficient patient‐centric smart contracts for healthcare ecosystems with access control capabilities

AbstractElectronic medical records are a patient's digital asset that enhances the information available to doctors for tracking their patients' health. When this information is stored in a secure environment, health examination reports can serve as a dependable repository for thorough observation of a patient's well‐being. However, it is crucial for the owner to have control over access to these repositories. In this scenario, a blockchain ecosystem with appropriate access control mechanisms can help create a distributed and decentralized storage platform to ensure the safety and security of data. Developing cost‐effective smart contracts and creating clear design diagrams to represent them are essential for establishing such an ecosystem. This paper introduces a smart contract for the Ethereum blockchain that allows an owner to maintain control over their data. The paper presents a diagram for visually representing the modules within our smart contract, providing readers with a clearer understanding of the access control techniques utilized in implementing our strategies. Our smart contract offers clinicians a valuable means of accessing historical data to promptly evaluate a patient's health in emergency situations. We showcase its efficacy by illustrating how it streamlines insurance claims, where it verifies the patient's coverage and automatically authorizes medical expense payments. Lastly, a study is presented to showcase an effective method of storing the ingested data within the Ethereum network. The suggested approach allows restrictions on data visibility based on the viewer's accessibility through identity‐based access control achieved using additional structures in smart contracts. These structures store filtered records accessible to users based on their viewing privileges. The simulated test bed results support the efficiency of using smart contracts with additional structures in terms of gas consumption when compared to those that use a single structure for read and write operations.

Privacy Preservation of Electronic Health Records in the Modern Era: A Systematic Survey

Building a secure and privacy-preserving health data sharing framework is a topic of great interest in the healthcare sector, but its success is subject to ensuring the privacy of user data. We clarified the definitions of privacy, confidentiality and security (PCS) because these three terms have been used interchangeably in the literature. We found that researchers and developers must address the differences of these three terms when developing electronic health record (EHR) solutions. We surveyed 130 studies on EHRs, privacy-preserving techniques, and tools that were published between 2012 and 2022, aiming to preserve the privacy of EHRs. The observations and findings were summarized with the help of the identified studies framed along the survey questions addressed in the literature review. Our findings suggested that the usage of access control, blockchain, cloud-based, and cryptography techniques is common for EHR data sharing. We summarized the commonly used strategies for preserving privacy that are implemented by various EHR tools. Additionally, we collated a comprehensive list of differences and similarities between PCS. Finally, we summarized the findings in a tabular form for all EHR tools and techniques and proposed a fusion of techniques to better preserve the PCS of EHRs.

Development of a security model for protecting the privacy of patients in a cloud-based information system

This work presents a security model in which medical professionals and other users can have access to patient’s health data stored in the cloud without knowledge of the identity of the particular patient which the database belongs to. The access control techniques used in this project grants classifier access to patient data, that is to say, it grants access to data based on the role of the data user. Thus, the aim and objective of the project is achieved.

Comparison of attribute-based encryption schemes in securing healthcare systems

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

A Literature Review on Access Control in Networking Employing Blockchain

Access Control (AC) in networking attempts to make sure that only authorized devices perform actions formed upon privileges defined for them with a view to prevent malicious users' entry and interaction in the communication grid. Blockchain solutions contain an arrangement of related blocks that naturally safeguards the trustworthiness, defending the incontestability, defend masked-identity of its transactions/transfers due to scattered consensus strategies and cryptographic solutions. Our survey comprehensively reviews BC-formed AC in broad scope of networking considering AC techniques while breaking down into 4 propositions and assessing them in terms of blockchain roles, AC technique and approach, network elements, and rest. We stockpiled a primary sample of 79 bibliographic references by weeding out them for screening criteria sought from scientific information reservoirs exploiting a qualitative and extensive strategy. Formed upon this survey, in blockchain-formed AC, blockchain can be exploited as an AC manager to administrate network devices and access information, implement automatic AC by means of smart contracts, secure storage of AC related data to reinforce overall AC security, and for safe data exchanging in the operation of AC. Minute assessment highlights that from blockchain-formed AC, 52.5% provide AC using blockchain itself or using smart contracts, 92.5% exploit sequential blockchain, 35% exploit PBFT consensus, provide 100% fine-grained and host-formed AC, 85% decentralized AC, 87.5% have single-factor authentication, 92.5% provide dynamic AC, and 45% have opted for IoT. Finally, we evaluate the chances and difficulties of the principle of blockchain-formed AC and then giving recommended actions to beat them.

Design and Analysis of a Bandwidth Aware Adaptive Multipath N-Channel Routing Protocol for 5G Internet of Things (IoT)

Large numbers of mobile wireless nodes that can move randomly and join or leave the network at any moment make up mobile ad-hoc networks. A significant number of messages are delivered during information exchange in populated regions because of the Internet of Things' (IoT) exponential increase in connected devices. Congestion can increase transmission latency and packet loss by causing congestion. More network size, increased network traffic, and high mobility that necessitate dynamic topology make this problem worse. An adaptive Multipath Multichannel Energy Efficient (AMMEE) routing strategy is proposed in this study, in which route selection strategies depend on forecasted energy consumption per packet, available bandwidth, queue length, and channel utilization. While multichannel uses a channel-ideal assignment process to lessen network collisions, multipath offers various paths and balances network strain. The link bandwidth is split up into a few sub-channels in the multichannel mechanism. To reduce network collisions, several source nodes simultaneously access the channel bandwidth. The cooperative multipath multichannel technique offers several paths from a single source or from several sources to the destination without colliding or becoming congested. The AMMEE routing approach is the basis for path selection. A load- and bandwidth-aware routing mechanism in the proposed AMMEE chooses the path based on node energy and forecasts their lifetime, which improves network dependability. The outcome demonstrates a comparative analysis of various multichannel medium access control (MMAC) techniques, including Parallel Rendezvous Multi Channel Medium Access Protocol (PRMMAC), Quality of Service Ad hoc On Demand Multipath Distance Vector (QoS-AOMDV), Q-learning-based Multipath Routing (QMR), and Topological Change Adaptive Ad hoc On-demand Multipath Distance Vector (TA-AOMDV) and the proposed AMMEE method. The results show that the AMMEE approach outperforms alternative systems. Doi: 10.28991/ESJ-2024-08-01-018 Full Text: PDF

A Blockchain-Based Trustworthy Access Control Scheme for Medical Data Sharing

Blockchain is commonly employed in access control to provide safe medical data exchange because of the characteristics of decentralization, nontamperability, and traceability. Patients share personal health data by granting access rights to users or medical institutions. The major purpose of the existing access control techniques is to identify users who are permitted to access medical data. They hardly ever recognize internal assailants from legitimate entities. Medical data will involve multilayer access within the authorized organizations. Considering the cost of permissions management and the problem of insider malicious node attacks, users hope to implement authorization constraints within the authorized institutions. It can prevent their data from being maliciously disclosed by end-users from different authorized healthcare domains. For the purpose to achieve the fine-grained permissions propagation control of medical data in sharing institutions, a trust-based authorization access control mechanism is suggested in this study. Trust thresholds are assigned to different privileges based on their sensitivity and used to generate zero-knowledge proof to be broadcasted among blockchain nodes. This method evaluates the trust of each user through the dynamic trust calculation model. And meanwhile, smart contract is employed to verify whether the user’s trust can activate some permissions and ensure the privacy of the user’s trust in the process of authorization verification. In addition, the authorization transaction between users and institutions is recorded on the blockchain for patient traceability and accountability. The feasibility and effectiveness of the scheme are demonstrated through comprehensive comparisons and extensive experiments.

Securing big graph databases: an overview of existing access control techniques

Securing big graph databases: an overview of existing access control techniques

Internet of Things (IoT) Increasing the Necessity to Adopt Specific Type of Access Control Technique

Internet of Things (IoT) Increasing the Necessity to Adopt Specific Type of Access Control Technique

Securing big graph databases: an overview of existing access control techniques

Securing big graph databases: an overview of existing access control techniques

Fine-Grained Encrypted Image Retrieval in Cloud Environment

With the growing emphasis on privacy awareness, there is an increasing demand for privacy-preserving encrypted image retrieval and secure image storage on cloud servers. Nonetheless, existing solutions exhibit certain shortcomings regarding retrieval accuracy, the capacity to search large images from smaller ones, and the implementation of fine-grained access control. Consequently, to rectify these issues, the YOLOv5 technique is employed for object detection within the image, capturing them as localized images. A trained convolutional neural network (CNN) model extracts the feature vectors from the localized images. To safeguard the encrypted image rules from easy accessibility by third parties, the image is encrypted using ElGamal. In contrast, the feature vectors are encrypted using the skNN method to achieve ciphertext retrieval and then upload this to the cloud. In pursuit of fine-grained access control, a role-based multinomial access control technique is implemented to bestow access rights to local graphs, thereby achieving more nuanced permission management and heightened security. The proposed scheme introduces a comprehensive cryptographic image retrieval and secure access solution, encompassing fine-grained access control techniques to bolster security. Ultimately, the experiments are conducted to validate the proposed solution’s feasibility, security, and accuracy. The solution’s performance across various facets is evaluated through these experiments.

KPI-HGNN: Key provenance identification based on a heterogeneous graph neural network for big data access control

Dynamic access control of big data has received much attention in recent years because of the characteristics of dynamic generation and multi-source aggregation of big data resources. Provenance-based access control defines dependency paths between resource states through provenance data, and it can dynamically realize access control according to different stages and states of resources. However, big data systems involve huge resources, and the state transition process is complex. The existing research on provenance-based access control techniques faces problems such as low efficiency of manually formulating dependency paths, redundant information in provenance data, and uneven distribution of resources. To solve these problems, this paper proposes a key provenance identification framework KPI-HGNN based on the heterogeneous graph neural network. In the framework, a community detection algorithm based on the heterogeneous graph neural network is designed to realize automatic identification and division of corresponding regions of big data resources through feature fusion of multiple types of nodes and edges. Meanwhile, a key node identification algorithm based on the heterogeneous graph attention network is designed to identify the key node in each community by weighted aggregation of the neighboring node attention coefficients. Besides, a key dependency path discovery algorithm is designed, and access control rules are automatically generated based on key dependency paths. The experimental results indicate that the community detection clustering index of the proposed method is better, the Top-5% key node identification accuracy is higher, and the resource coverage rate and the average percentage number product of key nodes of the provenance-based access control rules are better than those of the baseline method. These results indicate that the proposed key provenance identification framework can efficiently solve the problems in identifying key provenance information faced by dynamic access control of big data.

Identity and Access Control Techniques for Enhanced Data Communication in Cloud

The preservation of sensitive data and prevention of unauthorized access are critical objectives in cloud computing environments, necessitating the implementation of robust security measures. The present study delves into the amalgamation of the Hierarchical Role Based Access Control Model (HR-ACM), Composikey, a composite key encryption algorithm, and Interactive Tree Based zero knowledge protocol (ITZKP) to construct a robust security framework for cloud security. This study presents an investigation into the viability and efficacy of integrating HRACM, Composikey, and ITZKP as a means of augmenting security measures and reducing potential hazards in cloudbased systems. The execution times comparison of the Composikey, IBPRE, and KPRE models were compared for different filesizes (1 KB to 2 GB) to evaluate the performance of the HRACM method. As roles increase, RBAC a execution time increases significantly. The HRACM Method takes 0.001 to 0.002 seconds to implement across all role counts. The results show that the HRACM Method is more efficient and time-effective than the RBAC Method. The response time measured in microseconds for the existing ZKP and Libra systems for different file sizes, ranging from 1KB to 1 GB. The results reveal that the verifier time for the ITZKP system aligns closely with the existing systems, demonstrating its ability to perform efficient verification processes. These findings collectively demonstrate the potential of the integrated security framework in enhancing cloud security.

Mitigating Risks in the Cloud-Based Metaverse Access Control Strategies and Techniques

The advent of the metaverse has revolutionized virtual interactions and navigation, introducing intricate access control challenges. This paper addresses the need for effective access control models in the cloud-based metaverse. It explores its distinct characteristics, including its dynamic nature, diverse user base, and shared spaces, highlighting privacy concerns and legal implications. The paper analyzes access control principles specific to the cloud-based metaverse, emphasizing least privilege, separation of duties, RBAC, defense-in-depth, and auditability/accountability. It delves into identity verification and authorization methods, such as biometrics, multi-factor authentication, and role-based/attribute-based authorization. Advanced access control technologies for the cloud-based metaverse are examined, including SSO solutions, blockchain-based access control, ABAC, adaptive access control, and VMI for isolation. Risk mitigation strategies encompass IDS/IPS, SIEM, and user education programs.

Securing distributed systems: A survey on access control techniques for cloud, blockchain, IoT and SDN

Securing distributed systems: A survey on access control techniques for cloud, blockchain, IoT and SDN

PaaS platform security enhancement using fuzzy based access control and trust based signature

AbstractPlatform‐as‐a‐Service (PaaS) is one of the cloud computing services which will be offered to the clients through the virtualization platform. The problem is constructed in the PaaS platform effectively excluding internet service suppliers which do not meet highly secure standards, and so security issues can be a significant a hurdle to online computation. To address the aforementioned issues, the suggested method primarily concentrated proceeding the safety of PaaS infrastructure by using a novel fuzzy based access control technique, in which the information source is realized by using CDO security feature. To further enhance the security, security using trust based signature has been used in which the class and packet filter for each specified authorization were mapped to our class by modifying the security feature code. This public key will be utilized for authenticate that transaction relevant signature if the identity provider (IdP) has provided public safety data about this same two major components represents this little token on whose trusted trademark components are built put, that is, the entire item or even the claims contained. The suggested technique outperforms other current methods in terms of several performance parameters, with a high throughput of 14, CPU utilization of 12.5, and a low execution time of 5.2 s. The proposed ‘PaaS platform security enhancement with the use of fuzzy and trust‐based signatures’ provides high throughput and low execution time. This research work proposes a novel approach to enhancing the security of PaaS infrastructure, which is offered to clients through the virtualization platform in cloud computing. The current problem with PaaS is that it excludes internet service providers that do not meet high‐security standards, which poses a significant challenge to online computation. The suggested approach focuses on improving the safety of the PaaS platform by employing a fuzzy‐based access control technique, using the connectionless data objects security feature as the information source. To further strengthen security, the approach utilizes a trust‐based signature technique where the class and packet filter for each authorization are mapped to the class of the proposed method by modifying the security feature code. The proposed public key is then used to authenticate the transaction relevant signature, provided the IdP has given public safety data about these two components of the token on which Trusted Trademark components are built, that is, the entire item or even the claims contained within it. The proposed approach outperforms current methods in terms of several performance parameters, such as a high throughput of 14, a high CPU utilization of 12.5, and a low execution time of 5.2 s. In summary, the proposed PaaS platform security enhancement using fuzzy and trust‐based signatures provides an effective way to achieve high throughput and low execution time while ensuring platform security.