Robustness of ML-Enhanced IDS to Stealthy Adversaries
Authors: Vance Wong, John Emanuello | Published: 2021-04-21
脅威モデル
Towards Causal Federated Learning For Enhanced Robustness and Privacy
Authors: Sreya Francis, Irene Tenison, Irina Rish | Published: 2021-04-14
Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack
Authors: Luca Pajola, Mauro Conti | Published: 2021-04-13
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models
Authors: Neal Mangaokar, Jiameng Pu, Parantapa Bhattacharya, Chandan K. Reddy, Bimal Viswanath | Published: 2021-04-05
TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack
Authors: Yam Sharon, David Berend, Yang Liu, Asaf Shabtai, Yuval Elovici | Published: 2021-03-10
Secure Weighted Aggregation for Federated Learning
Authors: Jiale Guo, Ziyao Liu, Kwok-Yan Lam, Jun Zhao, Yiqiang Chen, Chaoping Xing | Published: 2020-10-17 | Updated: 2021-05-11
Security and Privacy Considerations for Machine Learning Models Deployed in the Government and Public Sector (white paper)
Authors: Nader Sehatbakhsh, Ellie Daw, Onur Savas, Amin Hassanzadeh, Ian McCulloh | Published: 2020-10-12
Clustering and Analysis of Vulnerabilities Present in Different Robot Types
Authors: Chinwe Ekenna, Bharvee Acharya | Published: 2020-08-18
Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities
Authors: Shuhan Yuan, Xintao Wu | Published: 2020-05-25
Can You Really Backdoor Federated Learning?
Authors: Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan | Published: 2019-11-18 | Updated: 2019-12-02