Network Anomaly Detection Using Transfer Learning Based on Auto-Encoders Loss Normalization. - Aviv Yehezkel; Eyal Elyashiv; Or Soffer (AISec@CCS, 2021)

A GNN-based Approach for Detecting Network Anomalies from Small Traffic Samples. - Aviv Yehezkel; Eyal Elyashiv (IEEE Big Data, 2022)

Using CFN for Uniform Sampling of Cloud-Native Datacenters. - Aviv Yehezkel; Eyal Elyashiv; Sharon Barkai (CCNC, 2022)

Towards a Global Anomaly Detector in High-speed Networks Where Traffic Sampling is a Necessity. - Aviv Yehezkel; Eldad Ohayon; Eyal Elyashiv (IEEE Big Data, 2024)

Finding an Optimal Small Sample of Training Dataset for Computer Vision Deep-Learning Models. - Aviv Yehezkel; Eyal Elyashiv (ICMLA, 2024)

Cybersecurity for Connected Vehicle Networks: Leveraging Sampled Network Traffic Beyond the CAN Protocol. - Aviv Yehezkel; Eyal Elyashiv (CSR, 2025)