Adversarial Examples: Attacks and Defenses for Deep Learning
Authors: Xiaoyong Yuan, Pan He, Qile Zhu, Xiaolin Li | Published: 2017-12-19 | Updated: 2018-07-07
When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time
Authors: David J. Miller, Yulia Wang, George Kesidis | Published: 2017-12-18 | Updated: 2018-06-28
Cyberattack Detection in Mobile Cloud Computing: A Deep Learning Approach
Authors: Khoi Khac Nguyen, Dinh Thai Hoang, Dusit Niyato, Ping Wang, Diep Nguyen, Eryk Dutkiewicz | Published: 2017-12-16
DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation
Authors: Catherine Wong | Published: 2017-12-14
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Authors: Wieland Brendel, Jonas Rauber, Matthias Bethge | Published: 2017-12-12 | Updated: 2018-02-16
Feature Extraction and Feature Selection: Reducing Data Complexity with Apache Spark
Authors: Dimitrios Sisiaridis, Olivier Markowitch | Published: 2017-12-11
Improving Malware Detection Accuracy by Extracting Icon Information
Authors: Pedro Silva, Sepehr Akhavan-Masouleh, Li Li | Published: 2017-12-10
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Authors: Battista Biggio, Fabio Roli | Published: 2017-12-08 | Updated: 2018-07-19
CycleGAN, a Master of Steganography
Authors: Casey Chu, Andrey Zhmoginov, Mark Sandler | Published: 2017-12-08 | Updated: 2017-12-16
Generative Adversarial Perturbations
Authors: Omid Poursaeed, Isay Katsman, Bicheng Gao, Serge Belongie | Published: 2017-12-06 | Updated: 2018-07-06