针对边缘设备的基于硬件的轻量级缓存侧通道攻击检测(Edge-CaSCADe)

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Transactions on Embedded Computing Systems Pub Date : 2024-05-11 DOI:10.1145/3663673
Pavitra Bhade, Joseph Paturel, Olivier Sentieys, Sharad Sinha
{"title":"针对边缘设备的基于硬件的轻量级缓存侧通道攻击检测(Edge-CaSCADe)","authors":"Pavitra Bhade, Joseph Paturel, Olivier Sentieys, Sharad Sinha","doi":"10.1145/3663673","DOIUrl":null,"url":null,"abstract":"<p>Cache Side Channel Attacks (CSCA) have been haunting most processor architectures for decades now. Existing approaches to mitigation of such attacks have certain drawbacks namely software mishandling, performance overhead, low throughput due to false alarms, etc. Hence, <i>“mitigation only when detected”</i> should be the approach to minimize the effects of such drawbacks. We propose a novel methodology of fine-grained detection of timing-based CSCA using a hardware-based detection module. </p><p>We discuss the design, implementation, and use of our proposed detection module in processor architectures. Our approach successfully detects attacks that flush secret victim information from cache memory like Flush+Reload, Flush+Flush, Prime+Probe, Evict+Probe, and Prime+Abort, commonly known as cache timing attacks. Detection is on time with minimal performance overhead. The parameterizable number of counters used in our module allows detection of multiple attacks on multiple sensitive locations simultaneously. The fine-grained nature ensures negligible false alarms, severely reducing the need for any unnecessary mitigation. The proposed work is evaluated by synthesizing the entire detection algorithm as an attack detection block, Edge-CaSCADe, in a RISC-V processor as a target example. The detection results are checked under different workload conditions with respect to the number of attackers, the number of victims having RSA,AES and ECC based encryption schemes like ECIES, and on benchmark applications like MiBench and Embench. More than \\(98\\% \\) detection accuracy within \\(2\\% \\) of the beginning of an attack can be achieved with negligible false alarms. The detection module has an area and power overhead of \\(0.9\\% \\) to \\(2\\% \\) and \\(1\\% \\) to \\(2.1\\% \\) for the targeted RISC-V processor core without cache for 1 to 5 counters, respectively. The detection module does not affect the processor critical path and hence has no impact on its maximum operating frequency.</p>","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"23 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lightweight Hardware-Based Cache Side-Channel Attack Detection for Edge Devices (Edge-CaSCADe)\",\"authors\":\"Pavitra Bhade, Joseph Paturel, Olivier Sentieys, Sharad Sinha\",\"doi\":\"10.1145/3663673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Cache Side Channel Attacks (CSCA) have been haunting most processor architectures for decades now. Existing approaches to mitigation of such attacks have certain drawbacks namely software mishandling, performance overhead, low throughput due to false alarms, etc. Hence, <i>“mitigation only when detected”</i> should be the approach to minimize the effects of such drawbacks. We propose a novel methodology of fine-grained detection of timing-based CSCA using a hardware-based detection module. </p><p>We discuss the design, implementation, and use of our proposed detection module in processor architectures. Our approach successfully detects attacks that flush secret victim information from cache memory like Flush+Reload, Flush+Flush, Prime+Probe, Evict+Probe, and Prime+Abort, commonly known as cache timing attacks. Detection is on time with minimal performance overhead. The parameterizable number of counters used in our module allows detection of multiple attacks on multiple sensitive locations simultaneously. The fine-grained nature ensures negligible false alarms, severely reducing the need for any unnecessary mitigation. The proposed work is evaluated by synthesizing the entire detection algorithm as an attack detection block, Edge-CaSCADe, in a RISC-V processor as a target example. The detection results are checked under different workload conditions with respect to the number of attackers, the number of victims having RSA,AES and ECC based encryption schemes like ECIES, and on benchmark applications like MiBench and Embench. More than \\\\(98\\\\% \\\\) detection accuracy within \\\\(2\\\\% \\\\) of the beginning of an attack can be achieved with negligible false alarms. The detection module has an area and power overhead of \\\\(0.9\\\\% \\\\) to \\\\(2\\\\% \\\\) and \\\\(1\\\\% \\\\) to \\\\(2.1\\\\% \\\\) for the targeted RISC-V processor core without cache for 1 to 5 counters, respectively. The detection module does not affect the processor critical path and hence has no impact on its maximum operating frequency.</p>\",\"PeriodicalId\":50914,\"journal\":{\"name\":\"ACM Transactions on Embedded Computing Systems\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Embedded Computing Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3663673\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Embedded Computing Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3663673","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0

摘要

数十年来,高速缓存侧通道攻击(CSCA)一直困扰着大多数处理器架构。现有的缓解此类攻击的方法存在一些缺陷,如软件处理不当、性能开销大、误报导致吞吐量低等。因此,"只有在检测到时才采取缓解措施 "应该是将这些缺点的影响降到最低的方法。我们提出了一种使用基于硬件的检测模块对基于时序的 CSCA 进行细粒度检测的新方法。我们讨论了我们提出的检测模块在处理器架构中的设计、实现和使用。我们的方法成功地检测出了从高速缓存中清除秘密受害者信息的攻击,如 Flush+Reload、Flush+Flush、Prime+Probe、Evict+Probe 和 Prime+Abort,即通常所说的高速缓存定时攻击。检测及时,性能开销最小。我们的模块中使用的计数器数量是可参数化的,可以同时检测多个敏感位置上的多种攻击。细粒度的特性确保了可忽略不计的误报,从而大大减少了不必要的缓解措施。以 RISC-V 处理器为例,通过将整个检测算法合成为攻击检测模块 Edge-CaSCADe,对提出的工作进行了评估。在不同的工作负载条件下,根据攻击者的数量、受害者的数量、基于RSA、AES和ECC的加密方案(如ECIES)以及基准应用程序(如MiBench和Embench)检查了检测结果。在攻击开始的(2%\)范围内,可以实现超过(98%\)的检测精度,误报率可以忽略不计。对于1到5个计数器的无缓存目标RISC-V处理器内核,检测模块的面积和功耗开销分别为(0.9%)到(2%)和(1%)到(2.1%)。检测模块不影响处理器的关键路径,因此对其最大工作频率没有影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Lightweight Hardware-Based Cache Side-Channel Attack Detection for Edge Devices (Edge-CaSCADe)

Cache Side Channel Attacks (CSCA) have been haunting most processor architectures for decades now. Existing approaches to mitigation of such attacks have certain drawbacks namely software mishandling, performance overhead, low throughput due to false alarms, etc. Hence, “mitigation only when detected” should be the approach to minimize the effects of such drawbacks. We propose a novel methodology of fine-grained detection of timing-based CSCA using a hardware-based detection module.

We discuss the design, implementation, and use of our proposed detection module in processor architectures. Our approach successfully detects attacks that flush secret victim information from cache memory like Flush+Reload, Flush+Flush, Prime+Probe, Evict+Probe, and Prime+Abort, commonly known as cache timing attacks. Detection is on time with minimal performance overhead. The parameterizable number of counters used in our module allows detection of multiple attacks on multiple sensitive locations simultaneously. The fine-grained nature ensures negligible false alarms, severely reducing the need for any unnecessary mitigation. The proposed work is evaluated by synthesizing the entire detection algorithm as an attack detection block, Edge-CaSCADe, in a RISC-V processor as a target example. The detection results are checked under different workload conditions with respect to the number of attackers, the number of victims having RSA,AES and ECC based encryption schemes like ECIES, and on benchmark applications like MiBench and Embench. More than \(98\% \) detection accuracy within \(2\% \) of the beginning of an attack can be achieved with negligible false alarms. The detection module has an area and power overhead of \(0.9\% \) to \(2\% \) and \(1\% \) to \(2.1\% \) for the targeted RISC-V processor core without cache for 1 to 5 counters, respectively. The detection module does not affect the processor critical path and hence has no impact on its maximum operating frequency.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ACM Transactions on Embedded Computing Systems
ACM Transactions on Embedded Computing Systems 工程技术-计算机:软件工程
CiteScore
3.70
自引率
0.00%
发文量
138
审稿时长
6 months
期刊介绍: The design of embedded computing systems, both the software and hardware, increasingly relies on sophisticated algorithms, analytical models, and methodologies. ACM Transactions on Embedded Computing Systems (TECS) aims to present the leading work relating to the analysis, design, behavior, and experience with embedded computing systems.
期刊最新文献
Multi-Traffic Resource Optimization for Real-Time Applications with 5G Configured Grant Scheduling Dynamic Cluster Head Selection in WSN Lightweight Hardware-Based Cache Side-Channel Attack Detection for Edge Devices (Edge-CaSCADe) Reordering Functions in Mobiles Apps for Reduced Size and Faster Start-Up NAVIDRO, a CARES architectural style for configuring drone co-simulation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1