Real-Time Detection for Cache Side Channel Attack using Performance Counter Monitor

Author:

Cho JonghyeonORCID,Kim Taehun,Kim Soojin,Im Miok,Kim Taehyun,Shin Youngjoo

Abstract

Cache side channel attacks extract secret information by monitoring the cache behavior of a victim. Normally, this attack targets an L3 cache, which is shared between a spy and a victim. Hence, a spy can obtain secret information without alerting the victim. To resist this attack, many detection techniques have been proposed. However, these approaches have limitations as they do not operate in real time. This article proposes a real-time detection method against cache side channel attacks. The proposed technique performs the detection of cache side channel attacks immediately after observing a variation of the CPU counters. For this, Intel PCM (Performance Counter Monitor) and machine learning algorithms are used to measure the value of the CPU counters. Throughout the experiment, several PCM counters recorded changes during the attack. From these observations, a detecting program was implemented by using these counters. The experimental results show that the proposed detection technique displays good performance for real-time detection in various environments.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference18 articles.

Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploit Detection and Mitigation Technique of Cache Side-Channel Attacks using Artificial Intelligence;2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS);2023-12-11

2. PMU-Spill: A New Side Channel for Transient Execution Attacks;IEEE Transactions on Circuits and Systems I: Regular Papers;2023-12

3. SpecWands: An Efficient Priority-Based Scheduler Against Speculation Contention Attacks;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-12

4. Design of Lightweight Cryptography based Deep Learning Model for Side Channel Attacks;2023 33rd International Telecommunication Networks and Applications Conference;2023-11-29

5. Exploration and Exploitation of Hidden PMU Events;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3