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Forensic Analysis of Blackhole Attack in Wireless Sensor Networks/Internet of Things

Hasan, Ahmad; Khan, Muazzam A.; Shabir, Balawal; Munir, Arslan; Malik, Asad Waqar; Anwar, Zahid; Ahmad, Jawad


Ahmad Hasan

Muazzam A. Khan

Balawal Shabir

Arslan Munir

Asad Waqar Malik

Zahid Anwar


The internet of things (IoT) is prone to various types of denial of service (DoS) attacks due to their resource-constrained nature. Extensive research efforts have been dedicated to securing these systems, but various vulnerabilities remain. Notably, it is challenging to maintain the confidentiality, integrity, and availability of mobile ad hoc networks due to limited connectivity and dynamic topology. As critical infrastructure including smart grids, industrial control, and intelligent transportation systems is reliant on WSNs and IoT, research efforts that forensically investigate and analyze the cybercrimes in IoT and WSNs are imperative. When a security failure occurs, the causes, vulnerabilities, and facts behind the failure need to be revealed and examined to improve the security of these systems. This research forensically investigates the performance of the ad hoc IoT networks using the ad hoc on-demand distance vector (AODV) routing protocol under the blackhole attack, which is a type of denial of service attack detrimental to IoT networks. This work also examines the traffic patterns in the network and nodes to assess the attack damage and conducts vulnerability analysis of the protocol to carry out digital forensic (DF) investigations. It further reconstructs the networks under different modes and parameters to verify the analysis and provide suggestions to design roubust routing protocols.

Journal Article Type Article
Acceptance Date Nov 3, 2022
Online Publication Date Nov 11, 2022
Publication Date 2022
Deposit Date Nov 23, 2022
Publicly Available Date Nov 23, 2022
Journal Applied Sciences
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 12
Issue 22
Article Number 11442
Keywords digital forensics; computer forensics; blackhole attack; wireless sensor network; forensic analysis; internet of things; network simulator (NS3)
Public URL


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