A detection mechanism on malicious nodes in IoT

Li, Bohan; Ye, Renjun; Gu, Gao; Liang, Ruochen; Liu, Wei; Cai, Ken

doi:10.1016/j.comcom.2019.12.037

Cited by 13 publications

(4 citation statements)

References 16 publications

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“…Also known as "malicious nodes,". It is a harmful attack on IoT's perception layer since its ability to disrupt networks, lose data, and violate privacy [29]. These fake nodes can be used to carry out various types of attacks, such as eavesdropping, data manipulation, or disrupting communication within the network and other nodes [15].…”

Section: Fake Nodesmentioning

confidence: 99%

“…Usually, maintaining a whitelist is easier, but large networks are better managed with blacklists. [29] proposes a method to detect malicious nodes in IoT networks using an online learning algorithm. The method involves calculating the credibility of each path on the network, modeling the reputation of the path, and detecting malicious nodes using a clustering algorithm.…”

Section: • Countermeasuresmentioning

confidence: 99%

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An Overview of Iot Architecture Security Issues and Countermeasures

Khalaifat

2024

AJRCoS

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The Internet of Things (IoT) has revolutionized the way we interact with our surroundings. As the number of IoT devices continues to increase, along with limited resources and diverse technologies, the risk of security attacks increases. Therefore, it is important to integrate security measures throughout the development process and system architecture. However, it is crucial to continually assess and update security measures to avoid emerging threats and ensure the confidentiality, integrity, and availability of IoT systems. This study aims to explore security issues in the IoT, highlighting the associated challenges. It examines various threats, attacks, and vulnerabilities that arise within a three-layer architecture and discusses potential solutions to enhance security in each layer. By addressing these concerns, it is possible to establish a secure and reliable foundation for expanding IoT systems.

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Section: Fake Nodesmentioning

confidence: 99%

Section: • Countermeasuresmentioning

confidence: 99%

An Overview of Iot Architecture Security Issues and Countermeasures

Khalaifat

2024

AJRCoS

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“…Li et al 63 introduced a novel method based on an online learning (OL) algorithm to detect malicious nodes. In this research study, the OL algorithm was used to discover each node's trust and then trained the model with the K‐means algorithm to classify nodes into malicious and benign nodes.…”

Section: Organization Of Iot Threat Detection Techniquesmentioning

confidence: 99%

Artificial intelligence empowered threat detection in the Internet of Things: A systematic review

Soltani

Rahmani

Bohlouli

et al. 2022

Concurrency and Computation

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Summary Internet of Things (IoT) is a new phenomenon that proposes novel business opportunities. IoT allows the world to be programmable and might provide several benefits for organizations. Based on the IoT survey, cyber‐security issues are among the most extensive and complicated challenges faced by IoT devices. Threat detection is considered a preventive measure against malware threats, ransomware, and attacks, which become more serious each year because of the dramatic rise in malware attacks. This article investigates threat detection techniques that fall into three categories: malware detection, attack detection, and ransomware detection, published from 2017 to August 2021. We examine solutions, techniques, features, classifiers, and tools proposed by IoT researchers. Some questions are proposed, and answering the questions may help the researchers suggest a more efficient solution in future works. Furthermore, the achievement and disadvantages of each study are discussed. Finally, based on the reviewed studies, some open challenges and practical measures to future directions are suggested, worth further studying and researching threat detection techniques in the IoT.

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“…Reference [ 46 ] proposes a malicious node detection method based on online learning algorithm. This method first calculates the credibility of each path in the network according to the collected data packets, then models the path reputation obtained through online learning algorithm, and calculates the trust of each node, and detects malicious nodes through the clustering algorithm.…”

Section: Common Applications Of Trustmentioning

confidence: 99%

Review on Security Issues and Applications of Trust Mechanism in Wireless Sensor Networks

Xia

Wei

Zhang

2022

Computational Intelligence and Neuroscience

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The scale of wireless sensor networks changes depending on specific application tasks. How to design a relatively simple security mechanism that can extend with the expansion of network scale is an arduous task. As the wireless sensor network mostly adopts the decentralized organization form, once the network nodes are distributed adequately, it is difficult to find out the failure of any node. In addition, the node has weak resistance to physical damage, so any node in the network may potentially become a cause of security vulnerability. In this study, firstly, the security standards that wireless sensor networks should have and the current security challenges faced by the network are discussed in detail, and the importance of security issues in wireless sensor networks is pointed out. Secondly, this paper studies and analyzes the current situation of wireless sensor network security problems including the internal and external attacks and the active and passive attacks. Thirdly, this paper also discusses the significance, concept, and characteristics of reputation and trust, the division and composition of reputation and trust system, and the common applications of the reputation and trust mechanism in wireless sensor networks.

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A detection mechanism on malicious nodes in IoT

Cited by 13 publications

References 16 publications

An Overview of Iot Architecture Security Issues and Countermeasures

An Overview of Iot Architecture Security Issues and Countermeasures

Artificial intelligence empowered threat detection in the Internet of Things: A systematic review

Review on Security Issues and Applications of Trust Mechanism in Wireless Sensor Networks

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