Threat Attribution

Cyber threat attribution aims to identify the perpetrators of cyberattacks, enabling effective countermeasures and legal action. Current research focuses on automating this process, moving beyond manual analysis by employing machine learning models, including graph neural networks and those leveraging natural language processing techniques like named entity recognition, often incorporating modular architectures to improve accuracy and interpretability. This work is crucial for enhancing cybersecurity defenses by improving the speed and accuracy of identifying attackers, ultimately leading to more effective mitigation strategies and deterrence.

Papers

October 15, 2024

Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning
Animesh Singh Basnet, Mohamed Chahine Ghanem, Dipo Dunsin, Wiktor Sowinski-Mydlarz
LeArning Abstract Deep Reinforcement Learning Deep Reinforcement Source Attribution Advanced Persistent Threat Malware Representation Behavioural Analysis Threat Attribution

August 9, 2024

AttackER: Towards Enhancing Cyber-Attack Attribution with a Named Entity Recognition Dataset
Pritam Deka, Sampath Rajapaksha, Ruby Rani, Amirah Almutairi, Erisa Karafili
Entity Recognition Named Entity Recognition Pseudo Victim AttackER Attack Attribution Threat Attribution

January 25, 2024

A Modular Approach to Automatic Cyber Threat Attribution using Opinion Pools
Koen T. W. Teuwen
Modular Approach Collective Human Opinion Opinion Aggregation Threat Attribution

July 17, 2023

A Machine Learning based Empirical Evaluation of Cyber Threat Actors High Level Attack Patterns over Low level Attack Patterns in Attributing Attacks
Umara Noor, Sawera Shahid, Rimsha Kanwal, Zahid Rashid
Machine Learning New Attack Intrusion Detection System Cyber Attack Empirical Evaluation Attack Pattern Attack Attribution Threat Attribution

June 25, 2022

Infinite Impulse Response Graph Neural Networks for Cyberattack Localization in Smart Grids
Osman Boyaci, M. Rasoul Narimani, Katherine Davis, Erchin Serpedin
Graph Neural Network Smart Grid Impulse Response Graph Neural Network Model Graph Signal Filter Threat Attribution

Threat Attribution

Papers

Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning

AttackER: Towards Enhancing Cyber-Attack Attribution with a Named Entity Recognition Dataset

A Modular Approach to Automatic Cyber Threat Attribution using Opinion Pools

A Machine Learning based Empirical Evaluation of Cyber Threat Actors High Level Attack Patterns over Low level Attack Patterns in Attributing Attacks

Infinite Impulse Response Graph Neural Networks for Cyberattack Localization in Smart Grids