Lightweight and secure authentication scheme for IoT network based on publish–subscribe fog computing model

Amanlou, Sanaz; Hasan, Mohammad Kamrul; Bakar, Khairul Azmi Abu

doi:10.1016/j.comnet.2021.108465

Cited by 61 publications

(31 citation statements)

References 41 publications

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“…Regarding studies that proposed security solutions, especially authentication for distributed MQTT architecture with multiple brokers, the authors in [23] presented a lightweight and secure authentication scheme for MQTT based on fog computing, which comprises multiple fog gateways as brokers. The scheme used the Elliptic Curve Diffie-Hellman Ephemeral (ECDHE) key exchange algorithm along with the pre-shared key (PSK).…”

Section: Related Workmentioning

confidence: 99%

A Multi-Tier MQTT Architecture with Multiple Brokers Based on Fog Computing for Securing Industrial IoT

Kurdi

Thayananthan

2022

Applied Sciences

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With the rapid growth of internet-connected devices and their resource-constrained capabilities, the current authentication mechanisms are unable to meet the complex IoT application requirements, such as in the Industrial Internet of Things (IIoT), due to the increased computation, communication, and storage overhead arising from these mechanisms. In the IIoT, machine-to-machine (M2M) communication is an underlying technology where devices (e.g., sensors, actuators, and controllers) can be enabled to exchange information autonomously; thus, the massive data generated by these devices can increase latency, network congestion, and the complexity of security management. Message queue telemetry transport (MQTT) is one of the promising M2M protocols used in the IoT that could encounter such issues because it relies on a central broker in the cloud and implements a heavyweight authentication mechanism based on TLS. Therefore, this paper proposes an MQTT architecture with multi-tier brokers based on fog computing, where each broker is deployed with an authentication manager. In addition, the paper presents a lightweight mutual authentication scheme based on hash function and XOR operation. Comparing the results given in the benchmark, the overall performance of our scheme shows that storage and communication overheads are reduced to 89% and 23%, respectively. Furthermore, our system can resist against several cyberattacks and provide scalability.

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Section: Related Workmentioning

confidence: 99%

A Multi-Tier MQTT Architecture with Multiple Brokers Based on Fog Computing for Securing Industrial IoT

Kurdi

Thayananthan

2022

Applied Sciences

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“…In addition, it is expected to build the hardware basics for wireless equipment through reconfigurable and smart materials [124]. Rundowns of ML device-to-device (D2D) communication, gigantic MIMP optimization, and heterogeneous organize plan are given in [125][126][127][128][129][130][131][132][133][134][135]. Counterfeit insights can move forward to organize execution based on its solid learning and capacity to think [133][134][135][136].…”

Section: Tends On 6g Iov ML and Aimentioning

confidence: 99%

Internet of vehicle's resource management in 5G networks using AI technologies: Current status and trends

et al. 2021

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The Internet of Vehicles (IoV) and Vehicle‐to‐Everything (V2X) concept have emerged from IoT technology, which refers to connecting many vehicles with various applications to the internet. The 5G new radio is based on a cloud‐radio access network (CRAN), considered as the communication infrastructure for IoV. However, due to the significant challenges and issues, researchers have been working on IoV and V2X. One of the main challenges for V2X is resource allocation and management for a high‐speed vehicular environment. This paper discusses and provides complete detail for resource allocation and management for IoV over 5G RAN networks focusing on artificial intelligence techniques. The paper also presented reviews on integrating the multi‐layers of vehicular network architecture with AI strategy to identify advancement and future directions for resource allocation and management issues.

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“…For instance, a Physical Clonable Functions (PUF)-based PUF-Cash Multiple Trusted Third Party (TTP) protocol is proposed for artificial intelligence (AI)-based Electronic Money [ 6 ], which leverages AI for the selection of an optimal subset of slave TTP for communication from the Master TTP for secure transaction. An extended Diffie–Hellman key exchange algorithm as a lightweight and secure authentication scheme based on MQTT subscribe and publish protocol is proposed for distributed fog computing in [ 7 ]. These software-based solutions address the issue of higher false alarms through changing the authentication protocol for the sensors.…”

Section: Introductionmentioning

confidence: 99%

Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach

Sahu

Davis

2022

Sensors

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False alerts due to misconfigured or compromised intrusion detection systems (IDS) in industrial control system (ICS) networks can lead to severe economic and operational damage. However, research using deep learning to reduce false alerts often requires the physical and cyber sensor data to be trustworthy. Implicit trust is a major problem for artificial intelligence or machine learning (AI/ML) in cyber-physical system (CPS) security, because when these solutions are most urgently needed is also when they are most at risk (e.g., during an attack). To address this, the Inter-Domain Evidence theoretic Approach for Inference (IDEA-I) is proposed that reframes the detection problem as how to make good decisions given uncertainty. Specifically, an evidence theoretic approach leveraging Dempster–Shafer (DS) combination rules and their variants is proposed for reducing false alerts. A multi-hypothesis mass function model is designed that leverages probability scores obtained from supervised-learning classifiers. Using this model, a location-cum-domain-based fusion framework is proposed to evaluate the detector’s performance using disjunctive, conjunctive, and cautious conjunctive rules. The approach is demonstrated in a cyber-physical power system testbed, and the classifiers are trained with datasets from Man-In-The-Middle attack emulation in a large-scale synthetic electric grid. For evaluating the performance, we consider plausibility, belief, pignistic, and general Bayesian theorem-based metrics as decision functions. To improve the performance, a multi-objective-based genetic algorithm is proposed for feature selection considering the decision metrics as the fitness function. Finally, we present a software application to evaluate the DS fusion approaches with different parameters and architectures.

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Lightweight and secure authentication scheme for IoT network based on publish–subscribe fog computing model

Cited by 61 publications

References 41 publications

A Multi-Tier MQTT Architecture with Multiple Brokers Based on Fog Computing for Securing Industrial IoT

A Multi-Tier MQTT Architecture with Multiple Brokers Based on Fog Computing for Securing Industrial IoT

Internet of vehicle's resource management in 5G networks using AI technologies: Current status and trends

Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach

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