Artificial Intelligence Methods for Cyber Threats Intelligence

AUTHOR(S):

Roumen Trifonov, Slavcho Manolov, Radoslav Yoshinov, Georgi Tsochev, Galya Pavlova

TITLE

Artificial Intelligence Methods for Cyber Threats Intelligence

ABSTRACT

Following ENISA's findings on the two main trends in Cyber Defence development over the past few years - adopting the philosophy and methods of Military Intelligence and introducing Artificial Intelligence into technologies for counteraction of cyber attacks - the Faculty of Computer Systems and Technology at Technical University of Sofia undertook research on the application of intelligent methods for increasing the security in computer networks. While in the field of Tactical Cyber Threats Intelligence the research has already passed into the real-world prototyping phase, in the sphere of Operational Cyber Threats Intelligence (as in the international research community) the research is still at an early stage

KEYWORDS

Cyber Threats Intelligence, Tactical, Operational, Artificial Intelligence, Multi-Agent Systems, Intrusion Detection and Prevention Systems, Behavioural Model, Machine Learning, Neural Networks, Reservoir Computing, Sequential Feature Selection

REFERENCES

[1] ENISA Threats Landscape Report 2016: 15 Top Cyber-Threats and Trends, January 2017

[2] Eric M. Hutchins, Michael J. Cloppert, Rohan M. Amin Intelligence-Driven Computer Network Defense Informed by Analysis of Adversary Campaigns and Intrusion Kill Chains Lockheed Martin Corporation 2015

[3] Republic of Bulgaria: National Cyber Security Strategy “Cyber Resilient Bulgaria 2020” 2016-03 NCSS Bulgaria final draft v 5 3

[4] Cyber Intelligence: Setting the Landscape for an emerging Discipline, Intelligence and National Security Alliance (INSA), 2011

[5] Operational Level of Cyber Intelligence, INSA, 2013

[6] Operational Cyber Intelligence, INSA, 2014

[7] Brian P. Kime Threat Intelligence: Planning and Direction, SANS Institute, 2015

[8] Advanced cyber-security intelligence, Quocirca, 2012

[9] Michael Luck, Peter McBurney, Christ Preist Agent Technology: Next Generation Computing, AgentLink II, January 2003

[10] S. D. Chi, J.S. Park, K.C. Jung and J.S. Lee Network Security Modeling and Cyber Attack Simulation Methodology, Lecture Notes in Computer Science, Vol. 2119, 2001

[11] V. Gorodetski, O. Karsayev, I. Kotenko, I. Khabalov Software Development Kit for MultiAgent System Design and Implementation, Lecture Notes in Artifical Intelligence, Vol. 2296, Springer Verlag, 2002

[12] Molesini, A., Omicini, A., and Viroli, M. Environment in agent-oriented software engineering methodologies, International Journal on Multiagent and Grid Systems, 2007

[13] G. Gai, L. Rui, H. Wu, X. Hu An Improved Collaborative Method for Recommendation and Rating Prediction, IEEE International Conference on Data Mining Workshop, 2014

[14] Jai Sundar Balasubramaniyan, Jose Omar Garcia-Fernandez.An Architecture for Intrusion Detection using Autonomous Agents, Purdue University West Lafayette, 2007

[15] Taraka D. Peddireddy Multiagent Network Security System using FIPA-OS, University of South Carolina, 2011

[16] D. Dasgupta, F. Gonzalez, K. Yallapu, J. Gomez, R. Yarramsettii CIDS: An agent-based intrusion detection system, The University of Memphis, 2014

[17] Trifonov R., Manolov S. Tsochev G. Application of multi-agent systems for network and information protection, 28th International Conference on Information Technologies (InfoTech 2014), Varna, Bulgaria

[18] Tsochev G, Trifonov R., Yoshinov R. Multiagent framework for intelligent networks, 29th International Conference on Information Technologies (Info-Tech 2015), Varna, Bulgaria

[19] Tsochev G, Trifonov R., Naydenov G. Agent Communication Languages Comparison, 7th International Scientific Conference COMPUTER SCIENCE’2015, Durres, Albania

[20] Tsochev G, Trifonov R., Popov G. A Security Model based on Multi-agent systems, 30th International Conference on Information Technologies (Info-Tech 2016), Varna, Bulgaria

[21] Liu Y., Sourina O. and Nguyen M. K. Realtime EEG-based human emotion recognition and visualization, Proceedings of the Int. Conf. on Cyberworlds (CW ’10), Singapore, 2010

[22] [RFC 1757 Remote Network Monitoring Management Information Base, Carnegie Mellon University, February 1995

[23] L. Bozhkov, P. Georgieva Classification models of emotional biosignals evoked while viewing affective pictures, International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH), Vienna, 2014

[24] Hammon P.S. and Sa V.R. de Preprocessing and meta-classification for brain-computer interfaces, IEEE Transactions on Biomedical Engineering, 54(3), 2007.

[25] Lukosevicius M. and Jaeger H. Reservoir computing approaches to recurrent neural network training, Computer Science Review, vol. 3, 2009

[26] Guyon I. and Elisseeff A. An Introduction to Variable and Feature Selection, Journal of Machine Learning Research, vol. 3, 2003

Cite this paper

Roumen Trifonov, Slavcho Manolov, Radoslav Yoshinov, Georgi Tsochev, Galya Pavlova. (2017) Artificial Intelligence Methods for Cyber Threats Intelligence. International Journal of Computers, 2, 129-135