133 citations · 195 across the 6 of their papers we have counts for
4 papers · 1 filter
On the Limitations of Continual Learning for Malware Classification
Mohammad Saidur Rahman, Scott E. Coull, Matthew Wright
Malicious software (malware) classification offers a unique challenge for continual learning (CL) regimes due to the volume of new samples received on a daily basis and the evoluti…
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection
Luca Demetrio, Scott E. Coull, Battista Biggio +3
Recent work has shown that adversarial Windows malware samples - referred to as adversarial EXEmples in this paper - can bypass machine learning-based detection relying on static c…
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers
Giorgio Severi, Jim Meyer, Scott Coull +1
Training pipelines for machine learning (ML) based malware classification often rely on crowdsourced threat feeds, exposing a natural attack injection point. In this paper, we stud…
Privacy Failures in Encrypted Messaging Services: Apple iMessage and Beyond
Scott Coull, Kevin Dyer
Instant messaging services are quickly becoming the most dominant form of communication among consumers around the world. Apple iMessage, for example, handles over 2 billion messag…