Distribution Awareness for AI System Testing

no code implementations • 6 May 2021 • David Berend

As Deep Learning (DL) is continuously adopted in many safety critical applications, its quality and reliability start to raise concerns.

TANTRA: Timing-Based Adversarial Network Traffic Reshaping Attack

no code implementations • 10 Mar 2021 • Yam Sharon, David Berend, Yang Liu, Asaf Shabtai, Yuval Elovici

Prior research on bypassing NIDSs has mainly focused on perturbing the features extracted from the attack traffic to fool the detection system, however, this may jeopardize the attack's functionality.

Network Intrusion Detection

Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers

no code implementations • 30 Oct 2020 • Tzvika Shapira, David Berend, Ishai Rosenberg, Yang Liu, Asaf Shabtai, Yuval Elovici

The performance of a machine learning-based malware classifier depends on the large and updated training set used to induce its model.

Malware Detection

Fair and accurate age prediction using distribution aware data curation and augmentation

2 code implementations • 11 Sep 2020 • Yushi Cao, David Berend, Palina Tolmach, Guy Amit, Moshe Levy, Yang Liu, Asaf Shabtai, Yuval Elovici

One of the main causes of unfair behavior in age prediction methods lies in the distribution and diversity of the training data.

Age Estimation Data Augmentation +3