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Found 6 papers, 5 papers with code
Learning with Holographic Reduced Representations
HRRs today are not effective in a differentiable solution due to numerical instability, a problem we solve by introducing a projection step that forces the vectors to exist in a well behaved point in space.
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection
Recent works within machine learning have been tackling inputs of ever-increasing size, with cybersecurity presenting sequence classification problems of particularly extreme lengths.
A New Burrows Wheeler Transform Markov Distance
Prior work inspired by compression algorithms has described how the Burrows Wheeler Transform can be used to create a distance measure for bioinformatics problems.
KiloGrams: Very Large N-Grams for Malware Classification
N-grams have been a common tool for information retrieval and machine learning applications for decades.
Non-Negative Networks Against Adversarial Attacks
Adversarial attacks against neural networks are a problem of considerable importance, for which effective defenses are not yet readily available.
Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus
As machine-learning (ML) based systems for malware detection become more prevalent, it becomes necessary to quantify the benefits compared to the more traditional anti-virus (AV) systems widely used today.
