Defeating Opaque Predicates Statically through Machine Learning and Binary Analysis
Authors: Ramtine Tofighi-Shirazi, Irina Asăvoae, Philippe Elbaz-Vincent, Thanh-Ha Le | Published: 2019-09-04
Feature Importance Analysis
KiloGrams: Very Large N-Grams for Malware Classification
Authors: Edward Raff, William Fleming, Richard Zak, Hyrum Anderson, Bill Finlayson, Charles Nicholas, Mark McLean | Published: 2019-08-01
Regularized adversarial examples for model interpretability
Authors: Yoel Shoshan, Vadim Ratner | Published: 2018-11-18 | Updated: 2018-11-21
Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternatives
Authors: Abhishek Divekar, Meet Parekh, Vaibhav Savla, Rudra Mishra, Mahesh Shirole | Published: 2018-11-13
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data
Authors: Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan | Published: 2018-05-31
Android Malware Detection based on Factorization Machine
Authors: Chenglin Li, Keith Mills, Rui Zhu, Di Niu, Hongwen Zhang, Husam Kinawi | Published: 2018-05-30 | Updated: 2019-08-13
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Authors: Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, Rory Sayres | Published: 2017-11-30 | Updated: 2018-06-07
A Unified Approach to Interpreting Model Predictions
Authors: Scott Lundberg, Su-In Lee | Published: 2017-05-22 | Updated: 2017-11-25
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Authors: Ruth Fong, Andrea Vedaldi | Published: 2017-04-11 | Updated: 2021-12-03
Learning Important Features Through Propagating Activation Differences
Authors: Avanti Shrikumar, Peyton Greenside, Anshul Kundaje | Published: 2017-04-10 | Updated: 2019-10-12