Central Pivot Heuristics for Botnet Attack Defense in Iot
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Abstract
Botnet assaults on IoT systems have become a big issue, and several strategies for botnet protection have been investigated by the academic and industry communities. While many of these methods are practical and effective for botnet attack prevention, one of the important limits is the load factor on the servers that manage monitoring and control in addition to catering to client system requests. To address load factor difficulties, the focus of this study report is on the conditions of installing a four-layer security control system based on the notion of central pivot points. Inspired by the effective and systematic Markov Chains concept, this publication proposes a four-layer filtering model that shows if botnet detection and prevention methods for servers are required. The model's simulated experimental study demonstrates the potential scope of deploying the system. The study also highlights the future possibilities of model improvisation that can reduce any erroneous signal production that is judged necessary.
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