Prof. Hussein Abbass

Artificial Intelligence - Autonomous Systems - Humans - Swarm - Trust

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Challenging systems to discover vulnerabilities using computational red teaming

DP140102590

Funding Organisation

Australian Research Council - Discovery Scheme

Funding Years

2014-2016

Chief Investigator

Hussein Abbass, UNSW-Canberra

Associated Research Fellows

Dr. Jiangjun Tang

Dr. George Leu

Associated Research Students

Ms. Aya Hussein, Ph.D., On Going

Ms. Marwa Hassan, M.Sc., Completed

Project Summary

Computational red teaming concerns the design of computational models to role play intelligent adversaries. These adversaries who are determined to exploit a system rely on creative thinking to discover system-level vulnerabilities by challenging system design, implementation or operations. This project closes a gap in the risk assessment literature by designing automated computational red teaming methods to discover vulnerabilities associated with intentional risks.

Authored Books

  1. Abbass H.A. (2015) Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems, Springer International Publishing Switzerland. ISBN 978-3-319-08280-6 (Hard Cover), 978-3-319-08281-3 (EBook), ISBN-10 3319082809,  DOI:10.1007/978-3-319-08281-3. 

Journals

  1. Greenwood G., Abbass H.A., and Petraki E. (2018). When is Altruistic Punishment Useful in Social Dilemmas?. BioSystems, 174, 60-62. DOI:doi.org/10.1016/j.biosystems.2018.10.015.
  2. Keshk, M., Singh, H., and Abbass H.A. (to appear) Automatic estimation of differential evolution parameters using Hidden Markov Models, Evolutionary Intelligence. DOI: 10.1007/s12065-018-0153-5 [PDF File]
  3. Tang, J., Leu, G. and Abbass, H.A. (2018) Networking the Boids is More Robust Against Adversarial Learning, IEEE Transactions on Network Science and Engineering. 5(2), 141-155. DOI: 10.1109/TNSE.2017.2745108. [PDF File]
  4. Wang, K., Bui, V., Petraki, E. and Abbass, H.A. (2018) Human-Guided Evolutionary Story Narration. IEEE Access, vol 6, 13783-13802. DOI: 10.1109/ACCESS.2018.2797879 [Open Access Full Paper available for Download for Free]
  5. Wang S.L., Shafi K., Ng T.F., Lokan C., Abbass H.A. (2017) Contrasting Human and Computational Intelligence Based Autonomous Behaviors in a Blue-Red Simulation Environment. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(1), 27-40. DOI:10.1109/TETCI.2016.2641929. [Open Access Full Paper available for Download for Free]
  6. Shafi K., Abbass H.A. (2017) A Survey of Learning Classifier Systems in Games. IEEE Computational Intelligence Magazine, 12, 42 - 55. DOI:10.1109/MCI.2016.2627670. [PDF File]
  7. Abbass, H. A., Leu, G., and Merrick, K. (2016). A Review of Theoretical and Practical Challenges of Trusted Autonomy in Big Data. IEEE Access, 4, 2808-2830. DOI:10.1109/access.2016.2571058. [Open Access Full Paper available for Download for Free]
  8. Abbass H.A., Petraki E., Merrick K., Harvey J., and Barlow M. (2016) Trusted Autonomy and Cognitive Cyber Symbiosis: Open Challenges. Cognitive Computation, 8(3), 385-408. 10.1007/s12559-015-9365-5.[Open Access Full Paper available for Download for Free]
  9. Abbass H.A., Greenwood G., and Petraki E. (2016) The N-Player Trust Game and its Replicator Dynamics. IEEE Transactions on Evolutionary Computation, 20(3), 470-474,. DOI:10.1109/TEVC.2015.2484840. [PDF File]
  10. Leu, G. and Abbass, H.A. (2016) A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human to Autonomous Eliciting Agents. Knowledge-Based Systems, 105, 1-22, August. DOI:10.1016/j.knosys.2016.02.012. [PDF File]

Conferences

  1. Tang J., Petraki E., Abbass H.A. (2016) Shaping Influence and Influencing Shaping: A Computational Red Teaming Trust-based Swarm Intelligence Model. International Conference on Swarm Intelligence, Bali, Indonesia, Springer International Publishing. 9712: 14-23. [Awarded Best Paper] [PDF File]
  2. Greenwood G., Abbass H.A., and Petraki E. (2016) Finite Population Trust Game Replicators, Australasian Conference on Artificial Life and Computational Intelligence, LNAI 9592, Springe-Verlag, pp. 324 - 335, 10.1007/978-3-319-28270-1_27. [PDF File]
  3. Leu, G., & Abbass, H. (2016). Computational Red Teaming in a Sudoku Solving Context: Neural Network Based Skill Representation and Acquisition. In Intelligent and Evolutionary Systems (pp. 319-332). Springer International Publishing.[PDF File]
  4. Petraki E. and Abbass H.A. (2014) On Trust and Influence: A Computational Red Teaming Game Theoretic Perspective. IEEE Computational Intelligence in Defence and Security Symposium, Hanoi, December 2014.[PDF File]
  5. Tang J. & Abbass H.A. (2014) Behavioral Learning of Aircraft Landing Sequencing Using a Society of Probabilistic Finite State Machines, IEEE WCCI, Beijing, China, pp. 610-617.[PDF File]

Outreach Activities

  1. Invited Speaker: The Australian Conference on Artificial Life and Computational Intelligence, Trusted Autonomy: Challenges and Opportunities for Computational Intelligence, 31-Jan to 2-Feb, Melbourne, 2017 [Youtube]
  2. Innovation Month, Department of Industry, Innovation and Science, August, 2015. [Youtube] [Transcript]
  3. Invited Speaker: The Seventh IEEE Symposium on Computational Intelligence for Security and Defense Applications , December, 14-17, 2014, Hanoi Vietnam, Computational Red Teaming for Cognitive-Cyber Symbiosis.
  4. Invited Speaker: The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, November, 10-12, 2014, Singapore, Real-time Computational Red Traming of Human Cognition using Encephalographic (EEG) Data.
  5. Invited Speaker: The Fourth International Neural Network Society Symposia Series , November, 7-9, 2014, Brunei, Next Generation Intelligent Systems: Observe-Project-Counteract Agent Architecture for Real-time Computational Red Teaming.
  6. Invited Lecture: Evolutionary Multi-objective Optimisation for Scenario Design and Real-time Optimisation, National University of Singapore, April 2014.
  7. Invited Seminar: Institute for Infocomm Research (I²R), Agency for Science, Technology and Research (A*STAR), March 25, 2014, Singapore, Computational Red Teaming for Integrating the Air Traffic Controller Brain and the Automation Cycle.
  8. Invited Seminar: Rolls-Royce, March 14, 2014, Singapore, Computational Red Teaming for Future Automation Systems.

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