Access Control In Internet Of Things Research Articles

A secure framework for effective workload resource management

An efficient and dynamic role-based access-control (RBAC) model is presented in this work which utilizes access-control for internet of things (IoT) nodes while minimizing storage and computational overhead. Also, for the identification of the malicious packets at the gateway server, a machine learning method has been presented. In addition, a framework for data management techniques in the IoT environment is designed to ensure efficient and secure storage, management, and processing of IoT data. The results have been evaluated by using the Montage and Cybershake workload in terms of energy consumption, processing time, detection accuracy and misclassification rate. The results show that the proposed secure framework for effective workload resource management (SFE-WRM) attains better performance in comparison to the reliable and energy‐efficient route selection (REERS) and FTA-WRM method. Also, by using the security method, the proposed method provides better security to the IoT nodes during the data aggregation and processing of the workload. The ultimate aim of this work is to provide a solution for the development of a secure and efficient IoT environment that can address critical security challenges and enable the widespread adoption of IoT devices and services.

A Hybrid Perspective on Threat Analysis and Activity-Based Attack Modeling for Strengthening Access Control in IoT

The rapid expansion of Internet of Things (IoT) devices has resulted in an unparalleled surge in the production of data and interconnectivity. Nevertheless, as IoT ecosystems become increasingly intricate, security concerns become of utmost importance, particularly in access control systems. The objective of this research is to improve the security of IoT access control by utilizing a hybrid model for analyzing threats and modeling attacks based on activities. This study has two primary objectives: a) A hybrid classification model is used to predict labels (attack or not) in binary classification with an impressive accuracy of 98.18%. b) Another hybrid classification model is employed to predict types of attacks in M2M communication, achieving a commendable accuracy of 90%. The primary goal is to create and assess a hybrid classification model for binary classification. This model will differentiate between regular system behavior and malicious attacks on access control schemes in the Internet of Things (IoT). The hybrid model, which combines the strengths of Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) networks, achieves an exceptional accuracy rate of 98.18%. The model's high accuracy demonstrates its effectiveness in precisely detecting potential threats and minimizing false positives, thereby establishing a strong basis for improving access control security. The second objective focuses on the complex area of security, with the goal of categorizing distinct forms of attacks in Machine-to-Machine (M2M) communication within the Internet of Things (IoT) framework. The hybrid classification model, employing both GRU and LSTM networks, achieves a remarkable accuracy of 90%. This accomplishment showcases the model's aptitude in detecting and distinguishing different types of attacks, including Distributed Denial of Service (DDoS) and Man-in-the-Middle attacks. The hybrid model provides security professionals with valuable insights to proactively respond to diverse threats in M2M communication by accurately classifying attack types. This strengthens the overall security posture of IoT access control systems. Overall, this study offers a thorough and efficient combination of threat analysis and activity-based attack modeling to enhance access control in IoT. The obtained accuracies in binary classification and prediction of attack types highlight the practical usability of the suggested hybrid model, establishing a strong basis for improving the security of IoT access control systems against evolving cyber threats

Zero Trust-Based Blockchain Based IoT Security with Consensus and Access Control Framework

As the Internet and computer technology develop, more gadgets are linked wirelessly, expanding the Internet of Things (IoT). IoT is a huge network of sensors and gateways that links them. IoT devices generate images, music, video, digital signals, and more by interacting with their surroundings. To exchange resources and information, all IoT equipment and apps may connect to the Internet. Everything is connected in our world. Due to the broad deployment and massive size of IoT devices, access control of device resources is problematic. Obtaining IoT device resources unlawfully will have major implications since they include personal and sensitive information. Many systems and situations employ access control technologies to secure resources. Discriminatory, identity-based, and MAC access control schemes are traditional (mandatory access control). However, these centralized methods have single-point failure, scalability issues, poor dependability, and low throughput. IoT devices may belong to several organizations or people, be mobile, and function badly, making centralized access management problematic. Another innovative data management solution is blockchain, which uses distributed storage to stabilize data. A transaction writes the data reading or modification record into a block, and the blocks are connected as a chain using a hash to maintain data integrity. It synchronizes data between nodes via a peer-to-peer network and consensus process, assuring data consistency for blockchain network participants. Zero Trust-Based Blockchain, an open source blockchain development platform, offers more efficient consensus methods, larger throughputs, smart contracts, and support for different organizations and ledgers. Proposed work build the fabric-IoT access control system using Zero Trust-Based Blockchain to apply blockchain technology to IoT access control in this study. Distributed processing and storage for IoT data may solve these critical issues with blockchain. Thus, developing distributed IoT-based e-healthcare services using blockchain technology may have been feasible. FabricIoT can keep records, handle dynamic access control, and solve the IoT access control problem using distributed architecture.

MSLShard: An efficient sharding-based trust management framework for blockchain-empowered IoT access control

The Internet of Things (IoT) is widely used in modern smart areas such as smart cities, but data security remains a significant challenge. Blockchain-based IoT access control addresses data security issues by preventing unauthorized devices from accessing limited IoT resources. However, most existing blockchain-based access control schemes still have scalability and security issues. A lightweight and secure framework, MSLShard, is proposed for the blockchain-based access control via sharding, which consists of two parts. First, an adaptive network sharding scheme based on network distance, node credibility, and access frequency is designed in the cloud-edge-end collaboration-based IoT architecture to reduce nodes' storage pressure and improve the scheme's scalability. Second, the trust management based on multidimensional subjective logic explicitly portrays the heterogeneity among edge nodes to motivate cooperation and further improve the security of the blockchain. Experimental results show that MSLShard can achieve high scalability and security in large-scale IoT environments compared to existing methods.

Secure Internet of Things (IoT) Networks: Study the challenges and develop solutions for securing IoT networks, including authentication, access control, and data protection

Secure Internet of Things (IoT) Networks: Study the challenges and develop solutions for securing IoT networks, including authentication, access control, and data protection

A survey on blockchain envisioned attribute based access control for internet of things: Overview, comparative analysis, and open research challenges

The Internet of Things (IoT) network is rapidly expanding due to sudden technological advancements, which enable objects to become intelligent and contribute to the network. Before permitting a newly added IoT device to communicate with the network, it is essential to provide access and authenticate the device’s legitimacy by ensuring that it has not been tampered. Recently, blockchain technology has been integrated into Attribute Based Access Control (ABAC) protocols to supply a more robust security mechanism for access control in IoT. The IoT and blockchain-based ABAC serve as the foundation of this survey, offering a comprehensive introduction to both topics. Additionally, several security concerns and vulnerabilities associated with Blockchain Envisioned ABAC (BE-ABAC) are presented. A Comparison with related surveys has also been made. Besides, we also present a comparative analysis based on evaluation based on Distance from Average Solution (EDAS) to rank the best schemes among the suggested BE-ABAC schemes. In conclusion, we discuss some open research challenges in an IoT network that uses blockchain to manage access control.

Enhanced Authentication for Decentralized IoT Access Control Architecture

The internet of things (IoT) enables a hyperconnected society, offering intelligent services and convenience through various connections between people, objects, and services. However, the current state of the IoT still faces limitations in security. Security issues in the IoT are of significant concern, leading to the proposal of numerous security frameworks and solutions to address these challenges. Authentication and authorization are crucial security requirements in the IoT environment, considering the potential risks posed by inadequate authentication and incorrect authorization. To comprehensively mitigate these issues, we presents a novel IoT access control architecture in this paper. The proposed architecture leverages the OAuth framework for authorization and the decentralized identity technology to enhance the authentication and authorization processes.

A Federated Attention-Based Multimodal Biometric Recognition Approach in IoT.

The rise of artificial intelligence applications has led to a surge in Internet of Things (IoT) research. Biometric recognition methods are extensively used in IoT access control due to their convenience. To address the limitations of unimodal biometric recognition systems, we propose an attention-based multimodal biometric recognition (AMBR) network that incorporates attention mechanisms to extract biometric features and fuse the modalities effectively. Additionally, to overcome issues of data privacy and regulation associated with collecting training data in IoT systems, we utilize Federated Learning (FL) to train our model This collaborative machine-learning approach enables data parties to train models while preserving data privacy. Our proposed approach achieves 0.68%, 0.47%, and 0.80% Equal Error Rate (EER) on the three VoxCeleb1 official trial lists, performs favorably against the current methods, and the experimental results in FL settings illustrate the potential of AMBR with an FL approach in the multimodal biometric recognition scenario.

IOT Assisted ECG Monitoring Framework with Secure Data Transmission Application

The growing Internet of Things (IoT) frame work enables us to create tiny devices that are capable of sensing processing and communicating, enabling sensors, embedding devices and other' things 'to be created which will help to understand the environment. In this paper, the IoT assisted electrocardiogram (ECG) monitoring framework with secure data transmission has been proposed in this research. With the proposed IoT assisted ECG monitoring system, the development and implementation of a light weight ECG Signal Strength Analysis has been proposed for automatic classification and real time implementation, using ECG sensors, Arduino, Android phones, Bluetooth and cloud servers. The Light weight Secure IoT (LS-IoT) and Light weight Access Control (LAC) have been introduced for asecuredatatypetransmission.Real-timeanalysisandverificationareperformedontheECGsignalsobtainedfromtheMIT-BI Hand Physio Net Challenges databases as well as the ECG signals for various physical activities. The potential for determining the clinical acceptability of ECG signals to increase the effectiveness, accuracy, and dependability of an unsupervised diagnostic system is significant in the proposed IoT assisted ECG monitoring framework.

Toward a Secure Smart-Home IoT Access Control Scheme Based on Home Registration Approach

The extensive application of the Internet of Things (IoT) and artificial intelligence technology has greatly promoted the construction and development of smart cities. Smart home as the foundation of smart cities can optimize home lifestyles. However, users access the smart home system through public channels, and the transmitted information is vulnerable to attack by attackers, and the privacy and data security of the home user will be difficult to be guaranteed. Therefore, how to protect users’ data and privacy security becomes critical. In this paper, we design a provably secure authentication scheme for the smart home environment, which ensures that only legitimate users can use smart devices. We use the informal model to verify the security of the scheme and formally analyze the security and correctness of the scheme through the Real or Random model. Finally, through the comparison of security and performance analysis, it is proven that our scheme has higher security under similar performance.

IoT Access Control Model Based on Blockchain and Trusted Execution Environment

With the application and popularization of the Internet of Things (IoT), while the IoT devices bring us intelligence and convenience, the privacy protection issue has gradually attracted people’s attention. Access control technology is one of the important methods to protect privacy. However, the existing IoT access control technologies have extensive problems such as coarse-grainedness, weak auditability, lack of access process control, and excessive privileges, which make the security and privacy of our IoT devices face great threats. Based on this, a blockchain-based and encrypted currency-based access control model CcBAC supported by Trusted Execution Environment (TEE) technology is proposed, which can provide fine-graininess, strong auditability, and access procedure control for the Internet of Things. In this study, the technical principle, characteristics, and research status of the control model are introduced, and the framework of the CcBAC model is expounded in detail and formally defined. Moreover, the functions in the model are described in detail, and a specific access control process in general scenarios is presented for the model. Finally, the practicability of this model is verified through theoretical analysis and experimental evaluation, which proves that this model not only enables resource owners to fully control the access to their resources, but also takes into account the fine-graininess and auditable access control.

Access Control for IoT: A Survey of Existing Research, Dynamic Policies and Future Directions.

Internet of Things (IoT) provides a wide range of services in domestic and industrial environments. Access control plays a crucial role in granting access rights to users and devices when an IoT device is connected to a network. However, many challenges exist in designing and implementing an ideal access control solution for the IoT due to the characteristics of the IoT including but not limited to the variety of the IoT devices, the resource constraints on the IoT devices, and the heterogeneous nature of the IoT. This paper conducts a comprehensive survey on access control in the IoT, including access control requirements, authorization architecture, access control models, access control policies, access control research challenges, and future directions. It identifies and summarizes key access control requirements in the IoT. The paper further evaluates the existing access control models to fulfill the access control requirements. Access control decisions are governed by access control policies. The existing approaches on dynamic policies' specification are reviewed. The challenges faced by the existing solutions for policies' specification are highlighted. Finally, the paper presents the research challenges and future directions of access control in the IoT. Due to the variety of IoT applications, there is no one-size-fits-all solution for access control in the IoT. Despite the challenges encountered in designing and implementing the access control in the IoT, it is desired to have an access control solution to meet all the identified requirements to secure the IoT.

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.

Blockchain-Based Access Control and Behavior Regulation System for IoT.

With the development of 5G and the Internet of things (IoT), the multi-domain access of massive devices brings serious data security and privacy issues. At the same time, most access systems lack the ability to identify network attacks and cannot adopt dynamic and timely defenses against various security threats. To this end, we propose a blockchain-based access control and behavior regulation system for IoT. Relying on the attribute-based access control model, this system deploys smart contracts on the blockchain to achieve distributed and fine-grained access control and ensures that the identity and authority of access users can be trusted. At the same time, an inter-domain communication mechanism is designed based on the locator/identifier separation protocol and ensures the traffic of access users are authorized. A feedback module that combines traffic detection and credit evaluation is proposed, ensuring real-time detection and fast, proactive responses against malicious behavior. Ultimately, all modules are linked together through workflows to form an integrated security model. Experiments and analysis show that the system can effectively provide comprehensive security protection in IoT scenarios.

Dynamic Access Control and Trust Management for Blockchain-Empowered IoT

The Internet of Things (IoT), while providing comprehensive interconnection and ubiquitous services, poses security issues by enabling resources sharing among various devices from different untrusted authorities. Blockchain, as a distributed ledger, provides a traceable and verifiable platform to ensure the secure access control in IoT. The existing works based on blockchain may bring up intolerable computing overhead and delay to the lightweight IoT devices. In this article, we propose a dynamic and lightweight attribute-based access control framework for blockchain-empowered IoT, to achieve secure and fine-grained authorization. The proposed scheme allows access to resources by evaluating attributes, operations, and the environment relevant to a request. The access policy is executed through smart contract in blockchain for security and flexibility. To further adapt to IoT device constraints, we design a access control framework based on decentralized application (DApp), which can maintain tamper proof in a timely manner and be adapt to the delay-intolerant application. When delay-intolerant access is required, access can be allowed according to local replica of the blockchain, without a consensus of blockchain network. Considering the time-varying attributes of IoT devices, a trust management scheme is proposed based on the Markov chain to resist the security fluctuation caused by the vulnerability of IoT devices. In the experiments, we deploy our system prototype on Ethereum to evaluate the feasibility and effectiveness of the scheme. The results show the proposed scheme can achieve secure, high throughput, and flexible access control in IoT.

RBAC-LBRM: An RBAC-Based Load Balancing Assisted Efficient Resource Management Framework for IoT-Edge-Fog Network

The inefficient handling of Internet of Things (IoT) network traffic may result in load-imbalance and unauthorized access, causing network performance degradation. The performance can be improved by off-loading some of the tasks to the network edge and fog layers. The existing works have discussed the issues of load balancing and access control in IoT using edge and fog environments; however, the design of an efficient resource management framework for an IoT-edge-fog environment is still under development. This work presents a role-based access control (RBAC)-based load balancing-assisted efficient resource management framework for IoT-edge-fog network named RBAC-LBRM. The overall average improvements of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">29.85, 16.82, 13.63, and 16.55%</i> have been achieved by RBAC-LBRM over other approaches w.r.t. CPU usage, memory usage, delay, and jitter metrics, respectively.

Exploiting Zero Knowledge Proof and Blockchains Towards the Enforcement of Anonymity, Data Integrity and Privacy (ADIP) in the IoT

In recent years, the Internet of Things (IoT) has been contemplated as the next technological advancement in the era of data communication and networking. However, although hundreds of new IoT platforms are introduced to the market every few months, the security of IoT ecosystems is still not fully understood. This paper discloses the architecture of a multilayer, multimode security system for the IoT. The proposed system is capable of providing multiple security solutions that support anonymous authentication, device privacy, data integrity, device sybil attack detection and IoT server spoofing attack detection. For IoT access control and authentication, our system can support two modes of operations, with one mode endorsing device privacy protection over the network and the second mode relinquishing device identity to establish data tracing during safety-critical IoT events. The new security system includes two innovative crypto approaches, zero knowledge proof (ZKP) and blockchains. IoT device anonymity was achieved via the multimode ZKP protocol, while data integrity and protection against sybil and IoT spoofing attacks were maintained via blockchains. Our threat analysis models showed that data modification and data injection attacks are not feasible. Probabilistic modeling of an IoT spoofing attack was performed in this paper, and the results show that our security system provides high resiliency against such attacks, with a probability approaching 1.

DAG blockchain-based lightweight authentication and authorization scheme for IoT devices

As the extension and expansion of the Internet, the Internet of things (IoT) connects things with the network through information sensing equipment to achieve intelligent identification, positioning, monitoring, management and other functions. With the increasing number of IoT users and devices, the demands for secure communication and data confidentiality are getting higher and higher, and the identity authentication and access control of IoT devices has become a huge challenge. In the IoT environment, the traditional device identity and access management methods based on public key infrastructure (PKI) and blockchain bring the problems of single point failure and scalability. The emergence of decentralized storage system and distributed ledger technology directed acyclic graph (DAG) provide new ideas to solve these problems. In the paper, we use distributed ledger technology IOTA with low energy demand to design a lightweight and scalable mechanism to manage the identity of IoT devices and access control of large-scale IoT data, so as to ensure source reliability and sharing security of IoT data. In the new scheme, IOTA technology is used to realize the functions of registration, update, revocation and retrieval of the identity of IoT devices, which solves the defects caused by centralized management. Inter planetary file system (IPFS) is used to store a large amount of data generated by devices in the IoT, which not only reduces the burden on devices and systems of IoT, but also solves the single point of failure, delay and other problems caused by traditional cloud storage. At the same time, the fog node is used to provide localized computing for a group of IoT devices to solve the problem of limited computing resources of IoT devices. In addition, in order to prevent data abuse caused by unauthorized devices accessing network resources, a trusted access control mechanism is designed to achieve fine-grained access control, access policy update and other functions, so as to better maintain the IoT environment and network security. Finally, the performance of the proposed scheme is evaluated through simulation experiments, and the security and functions of the scheme are analyzed, which proves that the scheme meets the security demands of the IoT environment.

IoT Device Integration and Payment via an Autonomic Blockchain-Based Service for IoT Device Sharing.

The Internet of Things (IoT) incorporates billions of IoT devices (e.g., sensors, cameras, wearables, smart phones, as well as other internet-connected machines in homes, vehicles, and industrial plants), and the number of such connected IoT devices is currently growing rapidly. This paper proposes a novel Autonomic Global IoT Device Discovery and Integration Service (which we refer to as aGIDDI) that permits IoT applications to find IoT devices that are owned and managed by other parties in IoT (which we refer to as IoT device providers), integrate them, and pay for using their data observations. aGIDDI incorporates a suite of interacting sub-services supporting IoT device description, query, integration, payment (via a pay-as-you-go payment model), and access control that utilise a special-purpose blockchain to manage all information needed for IoT applications to find, pay and use the IoT devices they need. The paper describes aGIDDI’s novel protocol that allows any IoT application to discover and automatically integrate and pay for IoT devices and their data that are provided by other parties. The paper also presents aGIDDI’s architecture and proof-of-concept implementation, as well as an experimental evaluation of the performance and scalability of aGIDDI in variety of IoT device integration and payment scenarios.

Decentralized Access Control using Blockchain Technology for Application in Smart Farming

The application of the Internet of Things (IoT) plays a crucial role in the fourth industrial revolution. The sophistication of technology due to the integration of heterogenous smart devices open a new threat from various aspects. Access control is the first line of defence to ensure that IoT resources are secure by preventing illegitimate users from gaining access to these resources. However, access control mechanisms face the limitation of technology in large scale IoT deployments since they are based on a centralized architecture. Significant research concerning decentralized access control solutions for securing IoT resources using combined techniques, such as blockchain, have caught much research attention in recent years. Nevertheless, research for decentralized access control for application in smart farming domain remain as a gap. Thus, this study presented a structured literature review on 81 articles related to the field of access control in IoT and blockchain technology to understand the challenges of centralized access control in securing IoT resources. This study serves as a foundation for decentralized access control using blockchain technology and its application to ensure the IoT actuators and sensors security with the aim to be applied in smart farming. This paper was deliberated based on systematic literature review that was searched from four different database platforms between 2018 and 2021. This study mostly addresses the relevant techniques/approaches including blockchain technology, access control model, key management mechanism and the combination of all three methods. The possible impacts, gap, procedures and evaluation of the decentralized access control are highlighted along with major trends and challenges.