DocumentCode :
2860684
Title :
Artificial intelligence application for improving cyber-security acquirement
Author :
Merat, Soorena ; Almuhtadi, Wahab
Author_Institution :
SC Eng. Inc., Ottawa, ON, Canada
fYear :
2015
fDate :
3-6 May 2015
Firstpage :
1445
Lastpage :
1450
Abstract :
The main focus of this paper is the improvement of machine learning where a number of different types of computer processes can be mapped in multitasking environment. A software mapping and modelling paradigm named SHOWAN is developed to learn and characterize the cyber awareness behaviour of a computer process against multiple concurrent threads. The examined process start to outperform, and tended to manage numerous tasks poorly, but it gradually learned to acquire and control tasks, in the context of anomaly detection. Finally, SHOWAN plots the abnormal activities of manually projected task and compare with loading trends of other tasks within the group.
Keywords :
learning (artificial intelligence); security of data; SHOWAN; anomaly detection; artificial intelligence application; computer process; concurrent threads; cyber awareness behaviour; cyber-security acquirement; machine learning; modelling paradigm; multitasking environment; software mapping; Artificial intelligence; Indexes; Instruction sets; Message systems; Routing; Security; Cyber Multitasking Performance; Cyber-Attack; Cyber-Security; Intrinsically locked; Non-maskable task; Normative Model; Queuing Management; Task Prioritization; synchronized thread;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on
Conference_Location :
Halifax, NS
ISSN :
0840-7789
Print_ISBN :
978-1-4799-5827-6
Type :
conf
DOI :
10.1109/CCECE.2015.7129493
Filename :
7129493
Link To Document :
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