Detecting Centralized Architecture-Based Botnets using Travelling Salesperson Non-Deterministic Polynomial-Hard problem, TSP-NP Technique
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The threats posed by botnets in the cyberspace continue to grow each day and it has become very hard to detect or infiltrate the cynicism of bots. This, is owing to the fact, that, the botnet developers each day, keep changing the propagation and attack techniques. Currently, most of these attacks have been centered on stealing computing energy, theft of personal information and Distributed Denial of Service (DDoS) attacks. In this paper, the authors propose a novel technique that uses the Non-Deterministic Polynomial-Time Hardness (NP-Hard Problem) based on the Traveling Salesperson Person (TSP) that depicts that a given bot, bj, is able to visit each host on a network environment, NE, and then it returns to the botmaster, in form of instruction(command), through optimal minimization of the hosts that are (may) be attacked. Given that bj represents a piece of malicious code and TSP-NP Hard Problem, which forms part of combinatorial optimization, the authors present this as an effective approach for the detection of the botnet. It is worth noting that the concentration of this study is basically on the centralized botnet architecture. This holistic approach shows that botnet detection accuracy can be increased with a degree of certainty and potentially decrease the chances of false positives. Nevertheless, a discussion on the possible applicability and implementation has also been given in this paper.
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