ZOU Jin-song. Mobile Malware Detection Model Based on Immune Danger Theory[J]. Journal of Southwest China Normal University(Natural Science Edition), 2018, 43(11): 78-85. doi: 10.13718/j.cnki.xsxb.2018.11.013
| Citation: |
ZOU Jin-song. Mobile Malware Detection Model Based on Immune Danger Theory[J]. Journal of Southwest China Normal University(Natural Science Edition), 2018, 43(11): 78-85. doi: 10.13718/j.cnki.xsxb.2018.11.013
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Mobile Malware Detection Model Based on Immune Danger Theory
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Putian Big Data Industrial College, Chongqing College of Water Resources and Electric Engineering, Yongchuan Chongqing 402160, China
More Information
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Received Date:
28/12/2017
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Abstract
In order to improve the adaptability and effectiveness of malware detection in mobile phones, a mobile malware detection model based on immune danger theory has been proposed in this paper. The model consists of four parts:data acquisition part, hazard signal generation part, co-stimulation signal generation part and warning part. Using differential method to express different dangerous signals, then the model produce corresponding co-stimulatory signals according to adaptive antigen presenting cells, and finally give early warning to malware. The experiment verifies the adaptability and effectiveness of this model.
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