Adversarial Artificial Intelligence

Research on developing robust and secure AI systems against malicious attacks

Adversarial Artificial Intelligence

Research on developing robust and secure AI systems against malicious attacks

AI systems can be fooled by adversarial attacks—carefully crafted inputs that cause wrong predictions. As AI powers healthcare, finance, and autonomous systems, protecting against manipulation is critical. We develop defenses that work across multiple domains.

Research Focus

Network Security

Encrypted traffic analysis detecting anomalies without breaking encryption. Real-time threat identification.

Mobile Security

Android malware detection resistant to evasion. Works even when attackers know our methods.

Healthcare AI

Medical diagnosis maintaining accuracy under attack. Patient prediction models resistant to manipulation.

Social Networks

Coordinated campaign detection. Bot identification and misinformation tracking.

Technical Approaches

Threat Detection

AI systems that identify adversarial patterns in encrypted traffic, mobile applications, and network communications. Zero-day attack detection using contrastive learning methods.

Robust Architecture

Privacy-preserving machine learning that protects data while maintaining model performance. System hardening protocols for mobile and network infrastructure.

Testing and Evaluation

Comprehensive adversarial testing frameworks. Performance metrics that measure resilience under attack conditions.

Impact

Our research contributes to securing AI systems in critical applications. Work includes encrypted traffic classification with high accuracy, mobile malware detection systems, and healthcare AI that maintains reliability under adversarial conditions.

Related Publications

2026

  1. Uncovering Microservice Faults: A Temporal Graph Approach to Root Cause Analysis
    2026
    Udi Aharon, Amit Dvir, Ran Dubin, Revital Marbel, and Chen Hajaj
    Proceedings of the IEEE International Conference on Communications. ICC 2026
  2. Real-Time Network Security: Integrating ANN and Dynamic Graph-Based Clustering
    2026
    Zohar Simhon, Matan Weiss, Revital Marbel, Chen Hajaj, Amit Dvir, and Ran Dubin
    Computer Networks
  3. Cleaner Adversarial CAPTCHAs: Intelligent Targets and Precise Noise for Usable Security
    2026
    Meir Litman, and Chen Hajaj
    Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026)

2025

  1. Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services’ User Anomalies
    2025
    Revital Marbel, Yanir Cohen, Ran Dubin, Amit Dvir, and Chen Hajaj
    Proceedings of the 34th International Conference on Computer Communications and Networks
  2. Optimized File Type Detection and One-Shot Reclassification Model
    2025
    Simona Lisker, Ayelet Botman, Chen Hajaj, Ran Dubin, and Amit Dvir
    Proceedings of the IEEE International Conference on Communications
  3. A New D-MAGIC: Dynamic Model for Cybersecurity Attack Detection Using GNNs into Clustering
    2025
    Zohar Simhon, Matan Weiss, Chen Hajaj, Revital Marbel, Ran Dubin, and Amit Dvir
    Proceedings of the IEEE International Conference on Communications
  4. PQClass: Classification of Post-Quantum Encryption Applications in Internet Traffic
    2025
    Angelos Marnerides, Chen Hajaj, Revital Marbel, Ran Dubin, and Amit Dvir
    Proceedings of the IEEE International Conference on Communications
  5. Leveraging OSINT for Advanced Proactive Cybersecurity: Strategies and Solutions
    2025
    Zafrir Avrahami, Moti Zwilling, and Chen Hajaj
    IEEE Access

2024

  1. Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services’ User Anomalies
    2024
    Revital Marbel, Yanir Cohen, Ran Dubin, Amit Dvir, and Chen Hajaj
    arXiv preprint arXiv:2409.12726
  2. Few-Shot API Attack Detection: Overcoming Data Scarcity with GAN-Inspired Learning
    2024
    Udi Aharon, Revital Marbel, Ran Dubin, Amit Dvir, and Chen Hajaj
    arXiv preprint arXiv:2405.11258
  3. Extending Limited Datasets with GAN-Like Self-Supervision for SMS Spam Detection
    2024
    Or Haim Anidjar, Revital Marbel, Ran Dubin, Amit Dvir, and Chen Hajaj
    Computers & Security

2023

  1. Breaking the Structure of MaMaDroid
    2023
    Harel Berger, Amit Dvir, Enrico Mariconti, and Chen Hajaj
    Expert Systems with Applications
  2. Adversarial Examples for Captcha Generation Adversarial Machine Learning for Social Good
    2023
    Chen Hajaj, and Meir Litman
    Available at SSRN 4608639
  3. Detecting Parallel Covert Data Transmission Channels in Video Conferencing Using Machine Learning
    2023
    Ofir Joseph, Avshalom Elmalech, and Chen Hajaj
    Electronics

2022

  1. MaMaDroid2.0–The Holes of Control Flow Graphs
    2022
    Harel Berger, Chen Hajaj, Enrico Mariconti, and Amit Dvir
    arXiv preprint arXiv:2202.13922
  2. Problem-Space Evasion Attacks in the Android OS: A Survey
    2022
    Harel Berger, Chen Hajaj, and Amit Dvir
    arXiv preprint arXiv:2205.14576
  3. Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks
    2022
    Harel Berger, Amit Dvir, Chen Hajaj, and Rony Ronen
    arXiv preprint arXiv:2205.04293
  4. Less Is More: Robust and Novel Features for Malicious Domain Detection
    2022
    Chen Hajaj, Nitay Hason, and Amit Dvir
    Electronics
  5. MalDIST: From Encrypted Traffic Classification to Malware Traffic Detection and Classification
    2022
    Ofek Bader, Adi Lichy, Chen Hajaj, Ran Dubin, and Amit Dvir
    2022 IEEE 19th annual consumer communications & networking conference (CCNC)

2021

  1. Crystal Ball: From Innovative Attacks to Attack Effectiveness Classifier
    2021
    Harel Berger, Chen Hajaj, Enrico Mariconti, and Amit Dvir
    IEEE Access
  2. Robust Coordination in Adversarial Social Networks: From Human Behavior to Agent-Based Modeling
    2021
    Chen Hajaj, Zlatko Joveski, Sixie Yu, and Yevgeniy Vorobeychik
    Network Science

2020

  1. Evasion Is Not Enough: A Case Study of Android Malware
    2020
    Harel Berger, Chen Hajaj, and Amit Dvir
    arXiv preprint arXiv:2003.14123
  2. Encrypted Video Traffic Clustering Demystified
    2020
    Amit Dvir, Angelos K Marnerides, Ran Dubin, Nehor Golan, and Chen Hajaj
    Computers & Security
  3. Evasion Is Not Enough: A Case Study of Android Malware
    2020
    Harel Berger, Chen Hajaj, and Amit Dvir
    International symposium on cyber security cryptography and machine learning
  4. Robust Malicious Domain Detection
    2020
    Nitay Hason, Amit Dvir, and Chen Hajaj
    Cyber Security Cryptography and Machine Learning: Fourth International Symposium, CSCML 2020, Be’er Sheva, Israel, July 2–3, 2020, Proceedings 4

2019

  1. Adversarial Coordination on Social Networks
    2019
    Chen Hajaj, Sixie Yu, Zlatko Joveski, and Yevgeniy Vorobeychik
    Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems
  2. Improving Robustness of ML Classifiers Against Realizable Evasion Attacks Using Conserved Features
    2019
    Liang Tong, Bo Li, Chen Hajaj, Chaowei Xiao, Ning Zhang, and Yevgeniy Vorobeychik
    28th USENIX Security Symposium (USENIX Security 19)

2018

  1. Adversarial task assignment
    2018
    Chen Hajaj, and Yevgeniy Vorobeychik
    International Joint Conference on Artificial Intelligence