Detecting and Assuaging Against Interest Flooding Attack Using Statistical Hypothesis Testing in Next Generation ICN

摘要

Information Centric Network (ICN) is a promising Internet Architecture designed for reliable content distribution which is built with named data objects. The content disseminating capability is decreased due to service poisoning attack like DDoS attack even when well-cache distribution policy is achieved. In order to improve the content delivery ratio and to reduce the processing delay we must be aware of Interest Flooding Attack (IFA) in ICN. Although myriad of solutions are introduced., none of them is helpful to prevent and mitigate the problem of flooding attack owing to lack of detection. The objective of the paper is to develop a secure routing policy which is congestion-free.,scalable and consumes minimal resource. In order to achieve this., we propose optimal Neyman Pearson detection method to reduce the workload of router and enhance the router performance. The detection is a preliminary part of IFA and it is based on statistical testing theory.lt intrinsically reduces the false alarm and missed detection probability. The experimental results of the proposed system prove the effectiveness in terms of reduced false alarm rate and missed detection rate. Further processing delay is reduced and content delivery ratio is increased.