DETECTION OF BOTNETS USING INVARIANT REPRESENTATION.

Over the past few decades, botnets are known to be a serious threat to the cyber security. The botnets are the systems in a particular network environment that are commanded by the attacker also known as Bot herder through C & C channel and hence targets the neighbour systems. As a result, several anomalies(such as DDoS, spamming, key-logging etc) are detected which leads to failure of the systems, information breach and also threat to security. With the advancement of technology, botnets tend to change their feature and pattern of attack and tend to be indomitable. In the proposed architecture, we derieved a methodology to effectively detect problematic botnets irrespective of their variance in features and attack pattern. Invariant representation is implemented to effectively detect the botnets and keep in view the feature of invariance and the architechture is evaluated using bin histogram representations and two-class SVM(Support Vector Machine).