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1
Vulnerability Assessment of the Rowhammer Attack Using Mach..:
, In:
Proceedings of the 2021 ACM Workshop on Secure and Trustworthy Cyber-Physical Systems
,
France, Loïc
;
Mushtaq, Maria
;
Bruguier, Florent
.. - p. 104-109 , 2021
Link:
https://dl.acm.org/doi/10.1145/3445969.3450425
RT T1 <cTitle>Proceedings of the 2021 ACM Workshop on Secure and Trustworthy Cyber-Physical Systems</cTitle>: T1 <Title>Vulnerability Assessment of the Rowhammer Attack Using Machine Learning and the gem5 Simulator - Work in Progress</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3450425&Exemplar=1&LAN=DE A1 France, Loïc A1 Mushtaq, Maria A1 Bruguier, Florent A1 Novo, David A1 Benoit, Pascal PB ACM YR 2021 K1 computer architecture K1 deep learning K1 dram K1 gem5 K1 machine-learning K1 neural networks K1 rowhammer K1 rowhammer detection K1 security K1 security assessments K1 Security and privacy K1 Security in hardware K1 Hardware attacks and countermeasures K1 Side-channel analysis and countermeasures SP 104 OP 109 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3445969.3450425 DO https://dl.acm.org/doi/10.1145/3445969.3450425 SF ELIB - SuUB Bremen
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