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Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems

5 July 2021

Papers citing "Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems"

30 / 30 papers shown

Title
On managing vulnerabilities in AI/ML systems Jonathan M. Spring April Galyardt A. Householder Nathan M. VanHoudnos 27 18 0 22 Jan 2021
Poisoning Attacks on Cyber Attack Detectors for Industrial Control Systems Moshe Kravchik Battista Biggio A. Shabtai AAML 59 28 0 23 Dec 2020
An Automated, End-to-End Framework for Modeling Attacks From Vulnerability Descriptions Hodaya Binyamini Ron Bitton Masaki Inokuchi T. Yagyu Yuval Elovici A. Shabtai 83 11 0 10 Aug 2020
Sponge Examples: Energy-Latency Attacks on Neural Networks Ilia Shumailov Yiren Zhao Daniel Bates Nicolas Papernot Robert D. Mullins Ross J. Anderson SILM 63 138 0 05 Jun 2020
Information Leakage in Embedding Models Congzheng Song A. Raghunathan MIACV 57 271 0 31 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 224 1,855 0 03 Mar 2020
Adversarial Machine Learning -- Industry Perspectives Ramnath Kumar Magnus Nyström J. Lambert Andrew Marshall Mario Goertzel Andi Comissoneru Matt Swann Sharon Xia AAML SILM 89 236 0 04 Feb 2020
Thesis Deployment Optimization of IoT Devices through Attack Graph Analysis Noga Agmon 26 20 0 15 Nov 2019
Extending Attack Graphs to Represent Cyber-Attacks in Communication Protocols and Modern IT Networks Orly Stan Ron Bitton Michal Ezrets Moran Dadon Masaki Inokuchi Yoshinobu Ohta Yoshiyuki Yamada T. Yagyu Yuval Elovici A. Shabtai 29 36 0 24 Jun 2019
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack Jianbo Chen Michael I. Jordan Martin J. Wainwright AAML 71 669 0 03 Apr 2019
Exploring Connections Between Active Learning and Model Extraction Varun Chandrasekaran Kamalika Chaudhuri Irene Giacomelli Shane Walker Songbai Yan MIACV 200 159 0 05 Nov 2018
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 77 458 0 03 Jul 2018
PRADA: Protecting against DNN Model Stealing Attacks Mika Juuti S. Szyller Samuel Marchal Nadarajah Asokan SILM AAML 70 442 0 07 May 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 85 763 0 01 Apr 2018
Query-Efficient Black-box Adversarial Examples (superceded) Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin AAML MLAU 68 53 0 19 Dec 2017
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 67 1,350 0 12 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 130 1,410 0 08 Dec 2017
Detection of Malicious and Low Throughput Data Exfiltration Over the DNS Protocol Asaf Nadler Avi Aminov A. Shabtai 20 100 0 25 Sep 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 99 633 0 29 Aug 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 127 1,782 0 22 Aug 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 83 1,882 0 14 Aug 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 131 1,864 0 20 May 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 266 4,152 0 18 Oct 2016
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library Nicolas Papernot Fartash Faghri Nicholas Carlini Ian Goodfellow Reuben Feinman ... David Berthelot P. Hendricks Jonas Rauber Rujun Long Patrick McDaniel AAML 65 513 0 03 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 545 5,909 0 08 Jul 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,682 0 08 Feb 2016
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 151 4,903 0 14 Nov 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,961 1 21 Dec 2013
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers G. Ateniese G. Felici L. Mancini A. Spognardi Antonio Villani Domenico Vitali 84 462 0 19 Jun 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 115 1,593 0 27 Jun 2012