Analysis Based on of Android Malicious Code Intrusion Detection

Article Preview

Abstract:

Due to the android platform is open source, more and more developers and manufacturers to use it. At the same time its security attracts more and more challenges, it is vulnerable to mobile phone virus attacks. In order to solve these problems, we should detect the files in the phone. Because the Boyer-Moore algorithms efficiency is higher than others, so we use it in android application intrusion detection. First we should set up a virus signature library, and store these signatures in the SQLite Database. Then scanning system of documents carries on the analysis and extraction corresponding feature codes, and use the BM algorithm to match them with virus signature, and we can find the viruses. What is new and original in this paper is that the efficiency of intrusion detection is higher.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

3924-3928

Citation:

Online since:

September 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Bangui, H., Alam, M., Khan, S. ET al. An Android runtime security policy enforcement framework [J]. Personal and ubiquitous computing, 2012, 16(6): 631-641.

DOI: 10.1007/s00779-011-0437-6

Google Scholar

[2] Informationon http: /www. netqin. com/security/securityinfo. jsp?id=4407.

Google Scholar

[3] Information on http: /www. source. android. com/tech/security.

Google Scholar

[4] Enck W, OngTang M, and Mc Daniel P . Understanding Android Security [J] IEEE Security and Privacy , 2009. 7: 50-57.

DOI: 10.1109/msp.2009.26

Google Scholar

[5] Xi gong Wu, Jie Ling. BM pattern matching algorithm analysis [J]. Computer engineering and design 28th January 2007 (1). 29-31 In Chinese.

Google Scholar

[6] Xigong Wu, Jie Ling. Single pattern matching algorithm [J]. J micro computer information. 22, 2006 8 - roll stage 3. 202-204 In Chinese.

Google Scholar

[7] A-ning Du, Bin-Xing Fang, Xiao-Chun Yun, etc. Comparison of String-matching Algorithms: An Aid to information content security. Proceedings of the Second International Conference on Mache Learning and Cybernetics, Xi'an, 2-5 November (2003).

DOI: 10.1109/icmlc.2003.1260090

Google Scholar

[8] Yang wan Cheng. Fast Virus Signature Matching based on the High Performance Computing of GPU. 2010 Second International Conference on Communication Software and Networks.

DOI: 10.1109/iccsn.2010.72

Google Scholar