A DoS Attack Effect Evaluation Method Based on Multi-source Data Fusion

Abstract

Existing DoS attack effect evaluation methods can be classified to two types based on attack types and attacked targets. We discuss their deficiencies on realisability, genaralization and index-relativity. From service requester's point of view, a new evaluation method is presented through single source detecting and multi-source data fusion. Algorithms aim at target types such as the node and the net are designed. And an evaluation model is built to test and verify the soundness of the algorithms. The results are more objective and effective, and meet the demands of remote evaluation.