DocumentCode :
1986610
Title :
Research on Intrusion Detection for Android Cell Phones Based on Snort
Author :
Xiaochun Liu ; Bo Yin ; Yongquan Yang ; Zhiqiang Wei
Author_Institution :
Coll. of Inf. Sci. & Eng., Ocean Univ. of China, Qingdao, China
Volume :
1
fYear :
2013
fDate :
28-29 Oct. 2013
Firstpage :
273
Lastpage :
276
Abstract :
With the rapid spread of the cell phones, more and more security threats against it appear. Nowadays people pay more attention to mobile phone security. Snort is a lightweight network intrusion detection system, and the multi-pattern matching algorithms it usually uses are AC algorithm and AC-BNFA algorithm. However, these algorithms are slow and take up too much memory. Now a new pattern matching algorithm is presented, which reduces the automaton states through transitions. The detection rate is ensured, the match rate is accelerated, the memory footprint is reduced, and the detection efficiency of the intrusion detection system is improved.
Keywords :
Android (operating system); computer network security; finite automata; pattern matching; smart phones; AC-BNFA algorithm; Android cell phones; Snort; automaton state reduction; detection efficiency improvement; intrusion detection rate; lightweight network intrusion detection system; match rate; memory footprint reduction; mobile phone security; multipattern matching algorithms; security threats; Algorithm design and analysis; Automata; Cellular phones; Intrusion detection; Pattern matching; Smart phones; Android; Snort; intrusion detection; pattern matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location :
Hangzhou
Type :
conf
DOI :
10.1109/ISCID.2013.75
Filename :
6804988
Link To Document :
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