A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs

Shehni, Rezvan Almas; Faez, Karim; Eshghi, Farshad; Kelarestaghi, Manoochehr

doi:10.3390/fi10010001

Cited by 12 publications

(2 citation statements)

References 26 publications

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“…Radio resource testing, RSSI and TDOA measure the physical layers described by Almas Shehni et al (2017) for the Sybil attack. RSSI and TDOA are two methods to locate Sybil Attack by measuring signal strength and the distance between beacons.…”

Section: Discussionmentioning

confidence: 99%

A survey of Sybil attack countermeasures in IoT-based wireless sensor networks

Arshad

Hanapi

Subramaniam

et al. 2021

PeerJ Computer Science

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Wireless sensor networks (WSN) have been among the most prevalent wireless innovations over the years exciting new Internet of Things (IoT) applications. IoT based WSN integrated with Internet Protocol IP allows any physical objects with sensors to be connected ubiquitously and send real-time data to the server connected to the Internet gate. Security in WSN remains an ongoing research trend that falls under the IoT paradigm. A WSN node deployed in a hostile environment is likely to open security attacks such as Sybil attack due to its distributed architecture and network contention implemented in the routing protocol. In a Sybil attack, an adversary illegally advertises several false identities or a single identity that may occur at several locations called Sybil nodes. Therefore, in this paper, we give a survey of the most up-to-date assured methods to defend from the Sybil attack. The Sybil attack countermeasures includes encryption, trust, received signal indicator (RSSI), encryption and artificial intelligence. Specifically, we survey different methods, along with their advantages and disadvantages, to mitigate the Sybil attack. We discussed the lesson learned and the future avenues of study and open issues in WSN security analysis.

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Section: Discussionmentioning

confidence: 99%

A survey of Sybil attack countermeasures in IoT-based wireless sensor networks

Arshad

Hanapi

Subramaniam

et al. 2021

PeerJ Computer Science

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“…The detection of a Sybil node is challenging based on the probability of two nodes having the same neighbours in a densely deployed network [21]. Similarly, in Reference [22], the authors have proposed a Sybil attack detection mechanism based on the principle that the RSS of the first legitimate node is low when it enters the radio range of a receiver. In Reference [23], an analytical model of Sybil attack detection in the IoT environment is provided.…”

Section: Related Workmentioning

confidence: 99%

A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks

Khan

Rehman

Yahya

et al. 2019

Sensors

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The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, that is, to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the medium access control (MAC) layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack.

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