Locality Based Cache Side-channel Attack Detection∗

doi:10.29007/vbqt

	Locality Based Cache Side-channel Attack Detection∗
	Wang, Limin 1; Bu, Lei 1; Song, Fu2
	2022
会议录名称	EPIC SERIES IN COMPUTING
卷号	87
页码	49-65
DOI	10.29007/vbqt
摘要	Cryptographic algorithms are fundamental to security. However, it has been shown that secret information could be effectively extracted through monitoring and analyzing the cache side-channel information (i.e., hit and miss) of cryptographic implementations. To mitigate such attacks, a large number of detection-based defenses have been proposed. To the best of our knowledge, almost all of them are achieved by collecting and analyzing hardware performance counter (HPC) data. But these low-level HPC data usually lacks semantic information and is easy to be interfered, which makes it difficult to determine the attack type by analyzing the HPC information only. Actually, the behavior of a cache attack is localized. In certain attack-related steps, the data accesses of cache memory blocks are intensive, while such behavior can be distributed sparsely among different attack steps. Based on this observation, in this paper, we propose the locality-based cache side-channel attack detection method, which combines the low-level HPC running data with the high-level control flow graph (CFG) of the program to achieve locality-guided attack pattern extraction. Then we can use GNN graph classification technology to learn such attack pattern and detect malicious attack programs. The experiments with a corpus of 1200 benchmarks show that our approach can achieve 99.44% accuracy and 99.47% F1-Score with a low performance overhead. © 2022, EasyChair. All rights reserved.
关键词	Benchmarking Cache memory Data flow analysis Flow graphs Semantics Attack detection Attack patterns Cryptographic algorithms Cryptographic implementation Hardware performance counters Hit and miss Secret information Semantics Information Side-channel attacks Side-channel information
会议名称	10th International Workshop on Security Proofs for Embedded Systems, PROOFS 2021
会议地点	Beijing, China
会议日期	September 17, 2021 - September 17, 2021
URL	查看原文
收录类别	EI
语种	英语
出版者	EasyChair
EI入藏号	20224613122817
EI主题词	Side channel attack
EISSN	2398-7340
EI分类号	722.1 Data Storage, Equipment and Techniques ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory
原始文献类型	Conference article (CA)
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/248927
专题	信息科学与技术学院_PI研究组_宋富组
通讯作者	Bu, Lei
作者单位	1.State Key Laboratory of Novel Software Techniques, Nanjing University, Jiangsu, Nanjing; 210023, China; 2.School of Information Science and Technology, ShanghaiTech University, Shanghai; 201210, China
推荐引用方式 GB/T 7714	Wang, Limin,Bu, Lei,Song, Fu. Locality Based Cache Side-channel Attack Detection∗[C]:EasyChair,2022:49-65.