Abstract
DDoS attacks are best detected near the victim’s site as the maximum attack traffic converges at this point. In most of current solutions, monitoring and analysis of traffic for DDoS detection have been carried at a single link which connects victim to Internet Service Provider (ISP). However the mammoth volume generated by DDoS attacks pose the biggest challenge in terms of memory and computational overheads. These overheads make DDoS solution itself vulnerable against DDoS attacks. We propose to distribute these overheads amongst all Points of Presences (POPs) of the ISP using an ISP level traffic feature distribution based approach. Entropy of incoming flows is taken as metric for traffic feature distribution. Entropy calculated from traffic monitored at all POPs, and total number of packets seen by every POP are then sent to the coordinating POP for final computation of entropy by our proposed formula. Here it is compared with normal entropy already profiled for the network environment. Thresholds are very carefully chosen keeping in mind fluctuations in traffic. We use an ISP level topology and well known attack tools for simulations in ns-2.
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