SocialSim

Computational Simulation of Online Social Behavior (SocialSim) program was focused on global information spread and its implications on national defense.

Applications:

Weaponization of Information Analysis and Prevention (operational setting)
Spread of Misinformation
Cognitive Cybersecurity (Industrial Application)

Cybersecurity

The goal was to simulate information spread and discussion the evolution around cyber attacks in order to gain valuable insights into how the community reacts to evolving cyber-threats. An example of the potential appications are discoveries from the simulation may lead to a quicker response to future attacks, e.g patching open source code on GitHub.

Cryptocurrency

The goal was to simulate information spread and discussion evolution around cryptocurrencies in order to gain valuable insights into the related social environments. Cryptocurrency’s surrounding environment of social and trading behavior are highly volatile and evolve quickly. Discoveries from simulation could be used to devise appropriate responses. An example event are pump and dump schemes.

Common Vulnerability Exposure and Exposure (CVE)

CVE’s are identifiers for publicly disclosed vulnerabilities in software. The goal was to simulate the spread of CVE related information. This information includes awareness of vulnerabilities and patches spread and are prioritized among the community of developers. Discoveries from simulation can help understand the factors which affect how security practices can become normalized into ordinary developer habits.

Skills Used

Worked in an interdisciplenary team that developed and analyzed agent based and deep learning models on the tasks associated with each category. Programming language used was Python for modelling and analysis. Data visualization skills commonly used to visualize model results and model functionality.

Papers

Schiappa, M., Chantry, G., & Garibay, I. (2019, October). Cyber Security in a Complex Community: A Social Media Analysis on Common Vulnerabilities and Exposures. In 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS) (pp. 13-20). IEEE.

Bidoki, N. H., Schiappa, M., Sukthankar, G., & Garibay, I. (2019). Predicting Social Network Evolution from Community Data Partitions. In International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation. Springer.

Page updated

Google Sites

Report abuse