Abstract
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.
Highlights
Advancement in sensing and hardware technologies have revolutionized computer systems to more perceive physical environment
The emergence of Internet of Things (IoT) can facilitate various aspects of people’s lives, most IoT devices are vulnerable to ransomware attacks (Yaqoob et al, 2017)
We proposed an IoT contact based on the concept of epidemiological concept that considers multihop IoT network and key transmission parameters in building model that can predict the susceptible, compromised and resistible IoT nodes along a connected path
Summary
Advancement in sensing and hardware technologies have revolutionized computer systems to more perceive physical environment. As part of suggestions to mitigate the menace of ransomware attacks, device users must be train to restart, switch off and upgrade device firmware Another suggestion is the deployment of layered defense strategy, in which ransomware are to be scan at multiple layer of a network (Castilho et al, 2017), (Hussain et al 2020) and (Stewart et al, 2017).
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More From: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
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