A MACHINE LEARNING APPROACH TO DETECT BOTNET TRAFFIC

Abstract

Botnet analysis aids in comprehending the attack concept and the aggressors' standard operating procedure. Botnet attacks are difficult to track due to their fast pace, pestilence nature, and smaller scale. When it comes to botnet assaults, AI is the only solution. It promotes location and aids in the prevention of bot attacks. The effective learning system will examine the client's digital behaviours and actions. It can undeniably discern the essence and scope of each activity by using online media. Nonetheless, the dark cap neighbourhood focuses solely on personal responsibility and spotlights on proliferating vindictive exercises. Botnets are probably the most pressing threat to our increasingly computerised society. By conducting a far-reaching botnet position and criminological analysis, the proposed probe model enhanced the nature of findings.