UPM Institutional Repository

IoTContact: a strategy for predicting contagious IoT nodes in mitigating ransomware attacks


Ibrahim, Mohammed and Abdullah, Mohd Taufik and Abdullah, Azizol and Perumal, Thinagaran (2021) IoTContact: a strategy for predicting contagious IoT nodes in mitigating ransomware attacks. Turkish Journal of Computer and Mathematics Education, 12 (3). 1957 - 1962. ISSN 1309-4653


Although the emergence of the Internet of Things (IoT) can facilitate various aspects of people’s lives, most IoT devices are vulnerable to ransomware attacks. Ransomware attacks in IoT networks can be more devastating due to its capability of affecting billions of interconnected devices. Ransomware can take control of compromised devices or an overall system and allow limited access to user interaction with IoT devices. Hence, there is a need for a strategy that can mitigate and predicts affected IoT devices to conduct in-depth forensic analysis in the event of a ransomware attack. This paper critically analyzes ransomware in IoT platforms and proposes IoTContact.IoTContact can formulate the mathematical model based on the interaction of multihop IoT devices and its relationship with ransomware. Consequently, it is expected that IoTContact can predict and classify affected IoT nodes into susceptible, compromise and resistible from the huge number of connected devices in the event of ransomware attacks. Therefore, the scope and the size of the object of forensic interest can be foreseen in preparation of an investigation.

Download File

Full text not available from this repository.

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.17762/turcomat.v12i3.1030
Publisher: Karadeniz Technical University
Keywords: Internet of things (IoT); Ransomware; Mathematical; Investigation
Depositing User: Ms. Che Wa Zakaria
Date Deposited: 12 Apr 2023 04:17
Last Modified: 12 Apr 2023 04:17
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.17762/turcomat.v12i3.1030
URI: http://psasir.upm.edu.my/id/eprint/93920
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item