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The Robust Malware Detection Challenge and Greedy Random Ac..:

, In: Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security,

Verwer, Sicco ; Nadeem, Azqa ; Hammerschmidt, Christian... - p. 61-70 , 2020

Link: https://dl.acm.org/doi/10.1145/3411508.3421374

RT 
T1 <cTitle>Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security</cTitle>: T1 <Title>The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3421374&Exemplar=1&LAN=DE
				
A1 Verwer, Sicco
A1 Nadeem, Azqa
A1 Hammerschmidt, Christian
A1 Bliek, Laurens
A1 Al-Dujaili, Abdullah
A1 O'Reilly, Una-May
PB ACM
YR 2020
K1 adversarial learning
K1 adversarial malware
K1 discrete optimization
K1 neural networks
K1 robust malware detection
K1 saddle-point optimization
K1 Security and privacy
K1 Intrusion/anomaly detection and malware mitigation
K1 Malware and its mitigation
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Reinforcement learning
K1 Adversarial learning
K1 Machine learning approaches
K1 Neural networks
K1 Artificial intelligence
K1 Search methodologies
K1 Discrete space search
K1 Randomized search
SP 61
OP 70
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3411508.3421374
DO https://dl.acm.org/doi/10.1145/3411508.3421374
SF ELIB - SuUB Bremen

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