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SoK: Explainable Machine Learning for Computer Security Applications

22 August 2022

Papers citing "SoK: Explainable Machine Learning for Computer Security Applications"

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Title
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language Model Yasir Ali Farrukh S. Wali I. Khan Nathaniel D. Bastian 445 2 0 27 Aug 2024
A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research Sicong Cao Xiaobing Sun Ratnadira Widyasari David Lo Xiaoxue Wu ... Jiale Zhang Bin Li Wei Liu Di Wu Yixin Chen 110 8 0 26 Jan 2024
Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster Clinton Cao Agathe Blaise S. Verwer Filippo Rebecchi 23 13 0 28 Jun 2022
The Role of Machine Learning in Cybersecurity Giovanni Apruzzese Pavel Laskov Edgardo Montes de Oca Wissam Mallouli Luis Brdalo Rapa A. Grammatopoulos Fabio Di Franco 73 137 0 20 Jun 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 116 20 0 31 May 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 248 195 0 03 Feb 2022
Learning to be adversarially robust and differentially private Jamie Hayes Borja Balle M. P. Kumar FedML 43 5 0 06 Jan 2022
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications Dongqi Han Zhiliang Wang Wenqi Chen Ying Zhong Su Wang Han Zhang Jiahai Yang Xingang Shi Xia Yin AAML 53 78 0 23 Sep 2021
FakeWake: Understanding and Mitigating Fake Wake-up Words of Voice Assistants Yanjiao Chen Yijie Bai Richard Mitev Kaibo Wang A. Sadeghi Wenyuan Xu AAML 56 21 0 21 Sep 2021
Research trends, challenges, and emerging topics of digital forensics: A review of reviews Fran Casino Thomas K. Dasaklis G. Spathoulas M. Anagnostopoulos Amrita Ghosal István Bor̈oc̈z A. Solanas Mauro Conti Constantinos Patsakis 65 84 0 10 Aug 2021
On the Importance of Domain-specific Explanations in AI-based Cybersecurity Systems (Technical Report) José Paredes J. C. Teze Gerardo Simari Maria Vanina Martinez 58 20 0 02 Aug 2021
A Survey on Data-driven Software Vulnerability Assessment and Prioritization T. H. Le Huaming Chen Muhammad Ali Babar 55 85 0 18 Jul 2021
Vulnerability Detection with Fine-grained Interpretations Yi Li Shaohua Wang Tien N Nguyen AAML 97 224 0 19 Jun 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 77 84 0 26 Apr 2021
To Trust or Not to Trust a Regressor: Estimating and Explaining Trustworthiness of Regression Predictions K. D. Bie Ana Lucic H. Haned FAtt 32 11 0 14 Apr 2021
Explainability-based Backdoor Attacks Against Graph Neural Networks Jing Xu Minhui Xue Xue S. Picek 75 76 0 08 Apr 2021
Efficient Training of Robust Decision Trees Against Adversarial Examples D. Vos S. Verwer AAML 50 36 0 18 Dec 2020
Towards falsifiable interpretability research Matthew L. Leavitt Ari S. Morcos AAML AI4CE 80 68 0 22 Oct 2020
What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors Yi-Shan Lin Wen-Chuan Lee Z. Berkay Celik XAI 88 97 0 22 Sep 2020
Why an Android App is Classified as Malware? Towards Malware Classification Interpretation Bozhi Wu Sen Chen Cuiyun Gao Lingling Fan Yang Liu W. Wen Michael R. Lyu 68 58 0 24 Apr 2020
Towards Quantification of Explainability in Explainable Artificial Intelligence Methods Sheikh Rabiul Islam W. Eberle S. Ghafoor XAI 63 43 0 22 Nov 2019
Towards Self-Explainable Cyber-Physical Systems Mathias Blumreiter Joel Greenyer Javier Chiyah-Garcia V. Klös Maike Schwammberger C. Sommer Andreas Vogelsang A. Wortmann 32 36 0 13 Aug 2019
The Price of Interpretability Dimitris Bertsimas A. Delarue Patrick Jaillet Sébastien Martin 50 34 0 08 Jul 2019
Treant: Training Evasion-Aware Decision Trees Stefano Calzavara Claudio Lucchese Gabriele Tolomei S. Abebe S. Orlando AAML 66 41 0 02 Jul 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 81 334 0 19 Jun 2019
VizADS-B: Analyzing Sequences of ADS-B Images Using Explainable Convolutional LSTM Encoder-Decoder to Detect Cyber Attacks Sefi Akerman Edan Habler A. Shabtai 72 18 0 19 Jun 2019
Proposed Guidelines for the Responsible Use of Explainable Machine Learning Patrick Hall Navdeep Gill N. Schmidt SILM XAI FaML 42 29 0 08 Jun 2019
Evaluating Explanation Methods for Deep Learning in Security Alexander Warnecke Dan Arp Christian Wressnegger Konrad Rieck XAI AAML FAtt 48 93 0 05 Jun 2019
Explainable Machine Learning for Scientific Insights and Discoveries R. Roscher B. Bohn Marco F. Duarte Jochen Garcke XAI 92 672 0 21 May 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 117 117 0 27 Feb 2019
Fairwashing: the risk of rationalization Ulrich Aïvodji Hiromi Arai O. Fortineau Sébastien Gambs Satoshi Hara Alain Tapp FaML 52 147 0 28 Jan 2019
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries Christian Scano Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 55 131 0 11 Jan 2019
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 123 172 0 03 Dec 2018
Learning Finite State Representations of Recurrent Policy Networks Anurag Koul S. Greydanus Alan Fern 46 88 0 29 Nov 2018
An Adversarial Approach for Explainable AI in Intrusion Detection Systems Daniel L. Marino Chathurika S. Wickramasinghe Milos Manic AAML 42 110 0 28 Nov 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 148 1,969 0 08 Oct 2018
Verification for Machine Learning, Autonomy, and Neural Networks Survey Weiming Xiang Patrick Musau A. Wild Diego Manzanas Lopez Nathaniel P. Hamilton Xiaodong Yang Joel A. Rosenfeld Taylor T. Johnson 72 102 0 03 Oct 2018
Automated Vulnerability Detection in Source Code Using Deep Representation Learning Rebecca L. Russell Louis Y. Kim Lei H. Hamilton Tomo Lazovich Jacob A. Harer Onur Ozdemir Paul M. Ellingwood M. McConley 68 534 0 11 Jul 2018
Explainable Security Luca Vigano Daniele Magazzeni SILM 56 74 0 11 Jul 2018
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 84 528 0 21 Jun 2018
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection Andy Brown Aaron Tuor Brian Hutchinson Nicole Nichols 37 173 0 13 Mar 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 130 1,409 0 08 Dec 2017
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples Gail Weiss Yoav Goldberg Eran Yahav 47 186 0 27 Nov 2017
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 157 683 0 26 Nov 2017
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 133 870 0 29 Oct 2017
Safe Reinforcement Learning via Shielding Mohammed Alshiekh Roderick Bloem Rüdiger Ehlers Bettina Könighofer S. Niekum Ufuk Topcu 82 691 0 29 Aug 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 163 2,160 0 21 Aug 2017
Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep Learning Andrew P. Norton Yanjun Qi AAML 48 47 0 01 Aug 2017
DeltaPhish: Detecting Phishing Webpages in Compromised Websites Igino Corona Battista Biggio M. Contini Luca Piras Roberto Corda Mauro Mereu Guido Mureddu Andrea Valenza Fabio Roli 74 80 0 02 Jul 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 252 4,273 0 22 Jun 2017