Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus. - William Fleshman; Edward Raff; Richard Zak; Mark McLean; Charles Nicholas (AAAI Fall Symposium: ALEC, 2018)

Hash-Grams On Many-Cores and Skewed Distributions. - Edward Raff; Booz Allen Hamilton; Mark McLean (IEEE BigData, 2018)

Non-Negative Networks Against Adversarial Attacks. - William Fleshman; Edward Raff; Jared Sylvester; Steven Forsyth; Mark McLean (CoRR, 2018)

An investigation of byte n-gram features for malware classification. - Edward Raff; Richard Zak; Russell Cox; Jared Sylvester; Paul Yacci; Rebecca Ward; Anna Tracy; Mark McLean; Charles Nicholas (J. Comput. Virol. Hacking Tech., 2018)

Barrage of Random Transforms for Adversarially Robust Defense. - Edward Raff; Jared Sylvester; Steven Forsyth; Mark McLean (CVPR, 2019)

KiloGrams: Very Large N-Grams for Malware Classification. - Edward Raff; William Fleming; Richard Zak; Hyrum S. Anderson; Bill Finlayson; Charles Nicholas; Mark McLean (CoRR, 2019)

A New Burrows Wheeler Transform Markov Distance. - Edward Raff; Charles Nicholas; Mark McLean (AAAI, 2020)

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection. - Edward Raff; William Fleshman; Richard Zak; Hyrum S. Anderson; Bobby Filar; Mark McLean (AAAI, 2021)

A spiking network model for semantic representation and replay-based association acquisition. - Brian S. Robinson; Adam Polevoy; Sean McDaniel; Will Coon; Clara A. Scholl; Mark McLean; Erik Johnson (ICONS, 2021)

Learning with Holographic Reduced Representations. - Ashwinkumar Ganesan; Hang Gao; Sunil Gandhi; Edward Raff; Tim Oates 001; James Holt; Mark McLean (NeurIPS, 2021)

An Easy Rejection Sampling Baseline via Gradient Refined Proposals. - Edward Raff; Mark McLean; James Holt (ECAI, 2023)