Pseudo Victim AttackER

Pseudo-victim attacker research focuses on understanding and mitigating the effectiveness of various attack strategies against machine learning models and systems. Current research explores diverse attack vectors, including manipulating audio signals (e.g., adding room reverberation to evade deepfake detection), injecting electromagnetic signals into cameras, poisoning training data with backdoors, and exploiting vulnerabilities in physical layer authentication. This work is crucial for improving the robustness and security of AI systems across numerous applications, from cybersecurity and authentication to autonomous systems and IoT devices, by informing the development of more resilient models and defenses.

Papers

July 18, 2022

Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniques
Clemens Sauerwein, Alexander Pfohl
Machine Learning Natural Language Processing Unstructured Text Automatic Classification Key Information Extraction Pseudo Victim AttackER

June 27, 2022

Measuring and Clustering Network Attackers using Medium-Interaction Honeypots
Zain Shamsi, Daniel Zhang, Daehyun Kyoung, Alex Liu
Measurement System Pseudo Victim AttackER Honeypot Interface Interaction Honeypot

June 15, 2022

Robust Attack Graph Generation
Dennis Mouwen, Sicco Verwer, Azqa Nadeem
Learned Model Product Automaton Attack Graph Distilled Model Pseudo Victim AttackER Automaton Model

May 24, 2022

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks
Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie, Xiaolin Huang
Adversarial Attack Adversarial Training Adversarial Perturbation Post Processing Pseudo Victim AttackER QuEry Based Attack Black Box Defense

December 21, 2021

What are Attackers after on IoT Devices? An approach based on a multi-phased multi-faceted IoT honeypot ecosystem and data clustering
Armin Ziaie Tabari, Xinming Ou, Anoop Singhal
Raw Data Constructive Approach Internet of Thing Internet of Thing Device Pseudo Victim AttackER Interaction Honeypot

Pseudo Victim AttackER

Papers

Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniques

Measuring and Clustering Network Attackers using Medium-Interaction Honeypots

Robust Attack Graph Generation

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks

What are Attackers after on IoT Devices? An approach based on a multi-phased multi-faceted IoT honeypot ecosystem and data clustering