  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.
