Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
Authors: Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg | Published: 2018-05-30
Attack Method
What we learn from learning – Understanding capabilities and limitations of machine learning in botnet attacks
Authors: David Santana, Shan Suthaharan, Somya Mohanty | Published: 2018-05-03
MEADE: Towards a Malicious Email Attachment Detection Engine
Authors: Ethan M. Rudd, Richard Harang, Joshua Saxe | Published: 2018-04-22
Neural Trojans
Authors: Yuntao Liu, Yang Xie, Ankur Srivastava | Published: 2017-10-03
On Security and Sparsity of Linear Classifiers for Adversarial Settings
Authors: Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli | Published: 2017-08-31
Coppersmith’s lattices and “focus groups”: an attack on small-exponent RSA
Authors: Stephen D. Miller, Bhargav Narayanan, Ramarathnam Venkatesan | Published: 2017-08-30 | Updated: 2020-12-16
Practical Attacks Against Graph-based Clustering
Authors: Yizheng Chen, Yacin Nadji, Athanasios Kountouras, Fabian Monrose, Roberto Perdisci, Manos Antonakakis, Nikolaos Vasiloglou | Published: 2017-08-29
Modular Learning Component Attacks: Today’s Reality, Tomorrow’s Challenge
Authors: Xinyang Zhang, Yujie Ji, Ting Wang | Published: 2017-08-25
Evasion Attacks against Machine Learning at Test Time
Authors: Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, Fabio Roli | Published: 2017-08-21
Learning Universal Adversarial Perturbations with Generative Models
Authors: Jamie Hayes, George Danezis | Published: 2017-08-17 | Updated: 2018-01-05