Automating Defense Against Adversarial Attacks: Discovery of Vulnerabilities and Application of Multi-INT Imagery to Protect Deployed Models

Authors: Josh Kalin, David Noever, Matthew Ciolino, Dominick Hambrick, Gerry Dozier | Published: 2021-03-29

Privacy and Trust Redefined in Federated Machine Learning

Authors: Pavlos Papadopoulos, Will Abramson, Adam J. Hall, Nikolaos Pitropakis, William J. Buchanan | Published: 2021-03-29 | Updated: 2021-03-30

CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks

Authors: Iqbal H. Sarker | Published: 2021-03-28

Graph Unlearning

Authors: Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang | Published: 2021-03-27 | Updated: 2022-09-16

Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks

Authors: Curtis G. Northcutt, Anish Athalye, Jonas Mueller | Published: 2021-03-26 | Updated: 2021-11-07

Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels — Attacks and Defenses

Authors: Saurav Maji, Utsav Banerjee, Anantha P. Chandrakasan | Published: 2021-03-26

Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G and Beyond

Authors: Brian Kim, Yalin E. Sagduyu, Tugba Erpek, Sennur Ulukus | Published: 2021-03-25

Black-box Detection of Backdoor Attacks with Limited Information and Data

Authors: Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu | Published: 2021-03-24

A Challenge Obfuscating Interface for Arbiter PUF Variants against Machine Learning Attacks

Authors: Yu Zhuang, Khalid T. Mursi, Li Gaoxiang | Published: 2021-03-24

CNN vs ELM for Image-Based Malware Classification

Authors: Mugdha Jain, William Andreopoulos, Mark Stamp | Published: 2021-03-24