WCSE 2021
ISBN: 978-981-18-1791-5 DOI: 10.18178/wcse.2021.06.033

AEMT: An Analytic Hierarchy Process-based Evaluation Model for IP Traceback

Hongcheng Tian, Jinting Dai, Shiyu Ji

Abstract— Distributed denial of service attacks continue to pose major threats to the Internet. Attackers often forge source addresses to escape detection, how to effectively trace the attackers back is an important issue of Internet security. Researchers have proposed various IP traceback schemes, but for these schemes, there exist some shortcomings in the aspects of computation overhead, storage overhead, traceback accuracy, traceback time and so on. Furthermore, in the field of IP traceback, comparisons among different IP traceback methods are mainly ones of multiple evaluation indexes one by one, and there does not exist an evaluation model (or an evaluation method) to comprehensively evaluate different schemes. The paper has proposed an analytic hierarchy process-based evaluation model for IP traceback (AEMT). Subsequently, the paper takes the network supervision department (an evaluator) and selecting a method under all scenes for the random deployment (a model target) for example, and applies AEMT to evaluate four typical traceback methods based on unified simulation experiments. In the end, the evaluation result conforms to the design and application characteristics of traceback methods. AEMT can supply the traceback field with an evaluation model, which can comprehensively quantitatively evaluate different traceback schemes

Index Terms— IP traceback, evaluation model, analytic hierarchy process

Hongcheng Tian
Medical Supplies Center, Chinese PLA General Hospital, CHINA
Jinting Dai
Zhengzhou University, CHINA
Shiyu Ji
Medical Supplies Center, Chinese PLA General Hospital, CHINA

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Cite: Hongcheng Tian, Jinting Dai, Shiyu Ji, "AEMT: An Analytic Hierarchy Process-based Evaluation Model for IP Traceback ," 2021 The 11th International Workshop on Computer Science and Engineering (WCSE 2021), pp. 224-228, Shanghai, China, June 19-21, 2021.