DocumentCode :
259627
Title :
Q-Learning: From Computer Network Security to Software Security
Author :
Randrianasolo, Arisoa S. ; Pyeatt, Larry D.
Author_Institution :
Sch. of Comput. & Inf., Lipscomb Univ., Nashville, TN, USA
fYear :
2014
fDate :
3-6 Dec. 2014
Firstpage :
257
Lastpage :
262
Abstract :
Reinforcement learning techniques become more popular in computer network security. The same reinforcement learning techniques developed for network security can be applied to software security as well. This research summarizes a work in progress attempt to incorporate Q-learning algorithm in software security. The Q-learning method is embedded as part of the software itself to provide a security mechanism that has ability to learn by itself to develop a temporary repair mechanism. The results of the experiment express that given the right parameters and the right setting the Q-learning approach rapidly learns to block all malicious actions. Data analysis on the Q-values produced by the software can provide security diagnostic as well. A larger scale experiment is expected to be seen in the future work.
Keywords :
computer network security; data analysis; learning (artificial intelligence); Q-learning; Q-values; computer network security; data analysis; malicious actions; reinforcement learning techniques; security diagnostic; software security; temporary repair mechanism; Connectors; Detectors; Learning (artificial intelligence); Maintenance engineering; Security; Software systems; Machine Learning; Q-Learning; Repair; Security; Software Architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2014 13th International Conference on
Conference_Location :
Detroit, MI
Type :
conf
DOI :
10.1109/ICMLA.2014.47
Filename :
7033124
Link To Document :
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