An intrusion detection system for the prevention of an active sinkhole routing attack in Internet of things

Tahir, Sabeen; Bakhsh, Sheikh Tahir; Alsemmeari, Rayan A.

doi:10.1177/1550147719889901

Cited by 12 publications

(14 citation statements)

References 17 publications

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“…In [57] Detection and prevention of sinkhole attack is countered by presenting prevention of an active sinkhole routing attack (PASR) based solution in which IoT clusters are built by network and connections are created between gateways and end devices. Sequence number is updated in route request message (RRM) to activate attack in ad hoc ondemand distance vector (AODV) protocol for testing purpose.…”

Section: ) Pasr Based Solution For Securitymentioning

confidence: 99%

A Review on the Security of IoT Networks: From Network Layer’s Perspective

et al. 2023

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Internet of Things (IoT) has revolutionized the world in the last decade. Today millions of devices are connected to each other utilizing IoT technology in one way or the other. With the significant growth in IoT devices, the provision of IoT security is imperative. Routing protocol for low power and lossy networks (RPL) is a network layer protocol, specially designed for routing in IoT devices. RPL protocol faces many attacks such as selective forwarding attacks, blackhole attacks, sybil attacks, wormhole attacks, and sinkhole attacks. All these attacks pose great threats to IoT networks and can substantially affect the performance of the network. In this work, a comprehensive review of internal attacks on the network layer is presented. Specifically, we focus on the literature that considers presenting solutions for the detection and prevention of sinkhole attacks. We reviewed the state-of-the-art works and different performance parameters like energy consumption, scalability, threshold value, packet delivery ratio, and throughput. Moreover, we also present a detailed analysis of machine learning-based algorithms and techniques proposed for the security of RPL protocol against internal attacks.

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Section: ) Pasr Based Solution For Securitymentioning

confidence: 99%

A Review on the Security of IoT Networks: From Network Layer’s Perspective

et al. 2023

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“…These attacks reduce the performance of targeted networks because the whole traffic of the IoT network flows towards the sinkhole. Still, this malicious node does not drop even a single message packet; they also harm the other performance-related attributes like efficiency and reliability of communication and disrupt the network protocols, especially the RPL protocol of IoT networks [114,115].…”

Section: Journal Of Sensorsmentioning

confidence: 99%

A Review of Security and Privacy Concerns in the Internet of Things (IoT)

et al. 2022

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The recent two decades have witnessed tremendous growth in Internet of things (IoT) applications. There are more than 50 billion devices connected globally. IoT applications’ connectivity with the Internet persistently victimized them with a divergent range of traditional threats, including viruses, worms, malware, spyware, Trojans, malicious code injections, and backdoor attacks. Traditional threats provide essential services such as authentication, authorization, and accountability. Authentication and authorization are the process of verifying that a subject is bound to an object. Traditional authentication and authorization mechanisms use three different factors to identity a subject to verify if the subject has the right capability to access the object. Further, it is defined that a computer virus is a type of malware. Malware includes computer viruses, worms, Trojan horses, spyware, and ransomware. There is a high probability that IoT systems can get infected with a more sophisticated form of malware and high-frequency electromagnetic waves. Purpose oriented with distinct nature IoT devices is developed to work in a constrained environment. So there is a dire need to address these security issues because relying on existing traditional techniques is not good. Manufacturers and researchers must think about resolving these security and privacy issues. Most importantly, this study identifies the knowledge and research gap in this area. The primary objective of this systematic literature review is to discuss the divergent types of threats that target IoT systems. Most importantly, the goal is to understand the mode of action of these threats and develop the recovery mechanism to cover the damage. In this study, more than 170 research articles are systematically studied to understand security and privacy issues. Further, security threats and attacks are categorized on a single platform and provide an analysis to explain how and to what extent they damage the targeted IoT systems. This review paper encapsulates IoT security threats and categorizes and analyses them by implementing a comparative study. Moreover, the research work concludes to expand advanced technologies, e.g., blockchain, machine learning, and artificial intelligence, to guarantee security, privacy, and IoT systems.

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“…The Sinkhole attack causes extensive threat, since it is a fundamental phase to launch additional attacks. Challenges exist in detecting, and providing resistance to a sinkhole attack in the WSN network [78][79][80][81].…”

Section: Iot Security Challenges In Different Layersmentioning

confidence: 99%

A Comprehensive Survey on Intrusion Detection based Machine Learning for IoT Networks

Mliki¹,

Kaceam²,

Fourati³

2021

ICST Transactions on Security and Safety

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The Internet of things (IoT) is a new ubiquitous technology that relies on heterogeneous devices and protocols. The IoT technologies are expected to offer a new level of connectivity thanks to its smart devices able to enhance everyday tasks and facilitate smart decisions based on sensed data. The IoT could collect sensitive data and should be able to face attacks and privacy issues. The IoT security issue is a hot topic of research and industrial concern. Indeed, threats against IoT devices and services could cause security breaches and data leakage. Aiming to identify attempts to abuse the IoT systems and mitigate malicious events, this paper studied the Intrusion Detection Systems (IDS) based on Machine Learning (ML) techniques. The ML approach could provide good tools to detect novel intrusion activities in a timely manner. This paper, therefore, highlighted the related issues to develop secured and efficient IoT services. It tried to allow a comprehensive review of IoT features and design. It mainly focused on intrusion detection based on the machine learning schema and built a taxonomy of different IoT attacks and threats. This paper also compared between the different intrusion detection techniques and established a taxonomy of machine leaning methods for intrusion detection solutions.

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An intrusion detection system for the prevention of an active sinkhole routing attack in Internet of things

Cited by 12 publications

References 17 publications

A Review on the Security of IoT Networks: From Network Layer’s Perspective

A Review on the Security of IoT Networks: From Network Layer’s Perspective

A Review of Security and Privacy Concerns in the Internet of Things (IoT)

A Comprehensive Survey on Intrusion Detection based Machine Learning for IoT Networks

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