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Journal Article
Mobile Malware Detection Using Correlational Analysis
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- Authors
- Seungyong Yoon, Jeongnyeo Kim, Hyunsook Cho
- Issue Date
- 2013-12
- Citation
- International Journal of Advancements in Computing Technology, v.5, no.16, pp.52-58
- ISSN
- 2005-8039
- Publisher
- 차세대융합기술연구원(AICIT)
- Language
- English
- Type
- Journal Article
- Abstract
- Currently, most of the smartphones use the method of the existing anti-virus program on your PC, such as the signature-based pattern matching techniques to detect the malicious code. When a new attack appears, this method cannot be detected before the attack signature updates. In addition, the performance problems act as the biggest disadvantage by the increasing number of malware signatures for attack detection. In this paper, to solve this problem, we propose the method of correlational analysis that use monitoring of user behavior, important information and resource access, telephone calls, SMS sending, and external network access without signature-based pattern matching techniques. Through this method, we can detect malicious activity on the smartphone illegal billing and information leakage.
- KSP Keywords
- Attack Detection, Attack signature, Correlational analysis, External Network, Malicious Activity, Malicious code, Matching techniques, Monitoring of user, Network access, Resource access, Signature-based