Botnet Detection Using Artificial Intelligence

Abstract

Over the last ten to fifteen years botnets have caught the attention of researchers worldwide. One of the dangerous additions to the gallery of malicious software programs is bot malware, popularly referred to as botnets. A botnet is a network of infected host/machines which can be functioning software program robots and are managed with the aid of a human, via one or more controllers. This chapter carried out a comparative evaluation of literature on previous researches and studies on botnet identity particularly using system language techniques. The examination revealed that the gain and popularity of machine learning algorithms in botnet detection stems from the fact that other styles of botnet detection strategies like the intrusion detection gadget had been visible to be externally incompetent. This chapter further proposes a botnet identification version using optics algorithm that hopes to effectively discover botnets and perceive the type of botnet detected by way of addition of latest feature; incorporation of changed traces to pinpoint supply IP of bot master, identification of existence of the kind of services the botnets get right of entry to are areas the proposed solution will cater to.