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