Dissecting Social Dynamics and Malware Attributions for Mitigating Network-centric Attacks
Abstract
PI seeks a novel solution using social dynamics analysis to counter network centric attacks as a complementary method to existing cyber defense technologies. The project goal is to create a comprehensive and effective analytical framework that can identify adversarial evidence by examining social dynamics. The project will have three main thrusts of work: 1) TASK 1: Data Collection and Management In this task, PI will collect real-world data and its multilingual contents and maintain corresponding repositories: underground hacking forums, identity theft forums and jihadi forums including English and non-English pages as well as malware attributions. 2) TASK 2: Cultivating Social Dynamics and Malware Attributions PI will apply and evaluate social ranking algorithms to the data set. PI will also apply user and group analysis to understand user and group dynamics and perform evidence mining by correlating social dynamics with adversarial events. 3) TASK 3: Developing and Testing Systematic Tools PI will design and implement a proof-of-concept prototype analysis system called SocialIntel and pilot test it.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1610129
Entities
People
- Gail-joon Ahn
Organizations
- Arizona State University
- Army Contracting Command
- United States Army