Defending against DDoS Attacks under IP Spoofing Using Image Processing Approach

抄録

This paper presents a novel defense scheme for DDoS attacks that uses an image processing method. This scheme especially focused on the prevalence of adjacent neighbor spoofing, called subnet spoofing. It is rarely studied and there is few or no feasible approaches than other spoofing attacks. The key idea is that a “DDoS attack with IP spoofing” is represented as a specific pattern such as a “line” on the spatial image planes, which can be recognized through an image processing technique. Applying the clustering technique to the lines makes it possible to identify multiple attack source networks simultaneously. For the identified networks in which the zombie hosts reside, we then employ a signature-based pattern extraction algorithm, called a pivoted movement, and the DDoS attacks are filtered by correlating the IP and media access control pairing signature. As a result, this proposed scheme filters attacks without disturbing legitimate traffic. Unlike previous IP traceback schemes such as packet marking and path fingerprinting, which try to diagnose the entire attack path, our proposed scheme focuses on identifying only the attack source. Our approach can achieve an adaptive response to DDoS attacks, thereby mitigating them at the source, while minimizing the disruption of legitimate traffic. The proposed scheme is analyzed and evaluated on the IPv4 and IPv6 network topology from CAIDA, the results of which show its effectiveness.