Adversarial Machine Learning Threat Analysis in Open Radio Access Networks. - Ron Bitton; Dan Avraham; Eitan Klevansky; Dudu Mimran; Oleg Brodt; Heiko Lehmann; Yuval Elovici; Asaf Shabtai (CoRR, 2022)

Exploiting Meta-Cognitive Features for a Machine-Learning-Based One-Shot Group-Decision Aggregation. - Hilla Shinitzky; Yuval Shahar; Dan Avraham; Yizhak Vaisman; Yakir Tsizer; Yaniv Leedon (CoRR, 2022)

Attacking Object Detector Using A Universal Targeted Label-Switch Patch. - Avishag Shapira; Ron Bitton; Dan Avraham; Alon Zolfi; Yuval Elovici; Asaf Shabtai (CoRR, 2022)

CADeSH Dataset: Collaborative Anomaly Detection for Smart Homes. - Yair Meidan; Dan Avraham; Hanan Libhaber; Asaf Shabtai (Zenodo, 2022)

D-Score: An expert-based method for assessing the detectability of IoT-related cyber-attacks. - Yair Meidan; Daniel Benatar; Ron Bitton; Dan Avraham; Asaf Shabtai (Comput. Secur., 2023)

CADeSH: Collaborative Anomaly Detection for Smart Homes. - Yair Meidan; Dan Avraham; Hanan Libhaber; Asaf Shabtai (IEEE Internet Things J., 2023)

Adversarial machine learning threat analysis and remediation in Open Radio Access Network (O-RAN). - Edan Habler; Ron Bitton; Dan Avraham; Eitan Klevansky; Dudu Mimran; Oleg Brodt; Heiko Lehmann; Yuval Elovici; Asaf Shabtai (J. Netw. Comput. Appl., 2025)