5 citations · 8 across the 2 of their papers we have counts for
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cs.CR2020
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification
Erwin Quiring, Lukas Pirch, Michael Reimsbach +2
Machine learning-based systems for malware detection operate in a hostile environment. Consequently, adversaries will also target the learning system and use evasion attacks to byp…
cs.CR2017★ 5 cited
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking
Erwin Quiring, Daniel Arp, Konrad Rieck
Machine learning is increasingly used in security-critical applications, such as autonomous driving, face recognition and malware detection. Most learning methods, however, have no…