Detecting App-DDoS Attacks Based on Marking Access and d-SVDD
In order to enhance the extensibility of current attack feature extracted and detection means for App-DDoS(Application Layer Distributed Denial of Service, App-DDoS) attacks, a novel feature extracted method based on marking access and a new detection algorithm named d-SVDD are proposed. After expressing kinds of App-DDoS attacks as characteristic vectors by access marked strategy and feature extracted strategy, d-SVDD algorithm is used for secondary classification and detection of pre-set area around decision boundary based on SVDD. It is proved by experiments that the proposed feature extracted and detection means can realize effective detection for kinds of App-DDoS attacks, both have satisfying time, space and extensibility performance.