| Abstract: | Botnet is a distributed platform for illegal activities severely threaten the security of the Internet. Fortunately, although their complicated nature, bots leave some footprints during the C&C communication that have been utilized by security researchers to design detection mechanisms. Nevertheless, botnet designers are always trying to evade detection systems by leveraging the legitimate P2P protocol as C&C channel or even mimicking legitimate peer‐to‐peer (P2P) behavior. Consequently, detecting P2P botnet in the presence of normal P2P traffic is one of the most challenging issues in network security. However, the resilience of P2P botnet detection systems in the presence of normal P2P traffic is not investigated in most proposed schemes. In this paper, we focused on the footprint as the most essential part of a detection system and presented a taxonomy of footprints utilized in behavioral P2P botnet detection systems. Then, the resilience of mentioned footprints is analyzed using three evaluation scenarios. Our experimental and analytical investigations indicated that the most P2P botnet footprints are not resilient to the presence of legitimate P2P traffic and there is a pressing need to introduce more resilient footprints. |
