2019年度 人工知能学会全国大会(第33回)

2019年度 人工知能学会全国大会(第33回)

2019年6月4日〜6月7日朱鷺メッセ 新潟コンベンションセンター
人工知能学会
2019年度 人工知能学会全国大会(第33回)

2019年度 人工知能学会全国大会(第33回)

2019年6月4日〜6月7日朱鷺メッセ 新潟コンベンションセンター

[3H3-E-3-01]An Autonomous Cooperative Randomization Approach to Prevent Attacks Based on Traffic Trends in the Communication Destination Anonymization Problem

〇Keita Sugiyama1, Naoki Fukuta1(1. Shizuoka University)
The communication destination anonymization problem is one of the problems to be resolved under some trade-offs in the cyber security field. Several approaches have been proposed for the communication destination anonymization problem such as Wang's U-TRI. However, due to the trade-offs that the user cannot take too expensive costs to make the network performance improved while keeping its security level, there remains the issues to make anonymization even over a short period of time while giving a good throughput. In this paper, we present an overview of the approach to solve this issue by introducing autonomously coordinating multiple end-hosts and a simulation environment to analyze it.