Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2015, Vol. 38 ›› Issue (4): 34-38.doi: 10.13190/j.jbupt.2015.04.008

• Papers • Previous Articles     Next Articles

Smartphone Malware Detection Model Based on Artificial Immune System in Cloud Computing

WU Bin1, LIN Xing1, LI Wei-dong2, LU Tian-liang3, ZHANG Dong-mei1   

  1. 1. Information Security Centre, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. Development Planning Department, State Grid Huaxian power supply company, Henan Anyang 456400, China;
    3. School of Network Security Defense, People's Public Security University of China, Beijing 100038, China
  • Received:2014-10-01 Online:2015-08-28 Published:2015-07-03

Abstract:

A smartphone malware detection model based artificial immune system(AIS) on the cloud was proposed. In this model, the extended negative selection algorithm is put forward and the antigens are generated by encoding the malwarecharacteristics. With addition of cloning with higher affinity detector and hyper-mutation, the detectors are generated efficiently. The computing rate is then improved significantly by parallel computing mechanism MapReduce during the feature coding and detector generation. Experimentshows that the detection modelhas a high detection rate and computing rate for unknown smartphone malware.

Key words: artificial immune system, negative selection, smartphone malware, detection, cloud computing

CLC Number: