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Found 7 papers, 3 papers with code
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
Machine learning (ML) plays a pivotal role in detecting malicious software.
Misleading Deep-Fake Detection with GAN Fingerprints
In particular, we show that an adversary can remove indicative artifacts, the GAN fingerprint, directly from the frequency spectrum of a generated image.
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification
Consequently, adversaries will also target the learning system and use evasion attacks to bypass the detection of malware.
Dos and Don'ts of Machine Learning in Computer Security
With the growing processing power of computing systems and the increasing availability of massive datasets, machine learning algorithms have led to major breakthroughs in many different areas.
Evaluating Explanation Methods for Deep Learning in Security
Deep learning is increasingly used as a building block of security systems.
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection.
Cryptography and Security
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking
This problem has motivated the research field of adversarial machine learning that is concerned with attacking and defending learning methods.
