On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

Authors: Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin | Published: 2019-07-26 | Updated: 2019-12-04

Semisupervised Adversarial Neural Networks for Cyber Security Transfer Learning

Authors: Casey Kneale, Kolia Sadeghi | Published: 2019-07-25

Anomaly-based Intrusion Detection in Industrial Data with SVM and Random Forests

Authors: Simon D. Duque Anton, Sapna Sinha, Hans Dieter Schotten | Published: 2019-07-24

Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier

Authors: Adam James Hall, Nikolaos Pitropakis, William J Buchanan, Naghmeh Moradpoor | Published: 2019-07-24

Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing

Authors: Yang Liu, Zhuo Ma, Ximeng Liu, Siqi Ma, Surya Nepal, Robert Deng | Published: 2019-07-24 | Updated: 2020-04-10

Enhancing Adversarial Example Transferability with an Intermediate Level Attack

Authors: Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge Belongie, Ser-Nam Lim | Published: 2019-07-23 | Updated: 2020-02-27

CAMLPAD: Cybersecurity Autonomous Machine Learning Platform for Anomaly Detection

Authors: Ayush Hariharan, Ankit Gupta, Trisha Pal | Published: 2019-07-23

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection

Authors: Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He | Published: 2019-07-23 | Updated: 2021-12-05

Characterizing Attacks on Deep Reinforcement Learning

Authors: Xinlei Pan, Chaowei Xiao, Warren He, Shuang Yang, Jian Peng, Mingjie Sun, Jinfeng Yi, Zijiang Yang, Mingyan Liu, Bo Li, Dawn Song | Published: 2019-07-21 | Updated: 2022-02-16

DaiMoN: A Decentralized Artificial Intelligence Model Network

Authors: Surat Teerapittayanon, H. T. Kung | Published: 2019-07-19