Proceedings of the 56th Annual Design Automation Conference 2019 2019
DOI: 10.1145/3316781.3317762
|View full text |Cite
|
Sign up to set email alerts
|

Adversarial Attack on Microarchitectural Events based Malware Detectors

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
10
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
4
3
1

Relationship

4
4

Authors

Journals

citations
Cited by 44 publications
(10 citation statements)
references
References 8 publications
0
10
0
Order By: Relevance
“…As described in the previous sections, I have been working and publishing papers on Malware Detection [6], Side-Channels Analysis [20,21], Hardware-based Trojan Attack and Detection [10], and Survey-based papers [43,44] published to conferences and journals. I intend to dive deeper into more of SCA based attacks and defenses in future and contribute my work to top tier conferences and journals.…”
Section: Research Progressmentioning
confidence: 99%
See 1 more Smart Citation
“…As described in the previous sections, I have been working and publishing papers on Malware Detection [6], Side-Channels Analysis [20,21], Hardware-based Trojan Attack and Detection [10], and Survey-based papers [43,44] published to conferences and journals. I intend to dive deeper into more of SCA based attacks and defenses in future and contribute my work to top tier conferences and journals.…”
Section: Research Progressmentioning
confidence: 99%
“…The hardware security domain in recent years has experienced a plethora of threats Side-Channel Attacks [1,2], Malware attacks [3][4][5][6][7][8][9], Hardware Trojan attacks [10], reverse engineering threats [11][12][13] and so on. Among multiple threats, the side-channel attacks (SCAs) is one of the pivotal threats due to it's capability to exploit the design despite being introduced in the market post-validation.…”
Section: Introductionmentioning
confidence: 99%
“…Table 1 [8,10,42]. Nevertheless, a recent work [11] presents that attackers can craft malware to bypass the detectors. We believe this problem also challenges SCAs detection.…”
Section: Comprehensive Study Of Machine Learning Classifiersmentioning
confidence: 99%
“…1 Lack of Robustness: Our comprehensive analysis shows that the previous works on SCAs detection jointly correlate the HPCs traces of victim and attack applications [8,42] where the detectors require HPCs data from both the attack and victim application. However, recent studies [2,11,15,17] show that attackers can craft [42] Yes Yes 100 -5000 No No mitigation module Real-Time Detection [9] No Yes 1. 5 2.4 No No mitigation module Nights-watch [25] No No No Mentioned No No mitigation module Cacheshield [3] No No [11][12][13][14][15][16][17][18][19][20][21][22][23][24] No mitigation module CPU Elasticity [23] No detection module No 32.66% No FLUSH+PREFETCH [24] No detection module No Not Mentioned No Random Fill [21] No detection module Yes No Mentioned No Catalyst [19] No attacks to bypass detectors.…”
Section: Introductionmentioning
confidence: 99%
“…The hardware security discipline in recent years experienced a plethora of threats like the Malware attacks [1,2,3,4,5,6,7], Side-Channel Attacks [8,9,10,11], Hardware Trojan attacks [12], reverse engineering threats [13,14,15] and so on. We focus on the malware detection technique here along with some state-of-the-art works.…”
Section: Introductionmentioning
confidence: 99%