引用本文:邹劲松.基于免疫危险理论的手机恶意软件检测模型[J].西南师范大学学报(自然科学版),2018,43(11):78~85
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基于免疫危险理论的手机恶意软件检测模型
邹劲松
重庆水利电力职业技术学院 普天大数据产业学院, 重庆 永川 402160
摘要:
为了提高智能手机恶意软件检测的自适应性和有效性,该文提出了基于免疫危险理论的手机恶意软件检测模型,该模型由4个部分组成:数据采集、危险信号生成、共刺激信号生成和预警部分,针对不同的恶意软件,采用微分方法表达危险信号,由自适应抗原提呈细胞产生相应的共刺激信号,最后对恶意软件产生预警.通过实验验证了该文模型的自适应性和有效性.
关键词:  智能手机  免疫危险理论  抗原提呈细胞  恶意软件检测
DOI:10.13718/j.cnki.xsxb.2018.11.013
分类号:TP391
基金项目:
Mobile Malware Detection Model Based on Immune Danger Theory
ZOU Jin-song
Putian Big Data Industrial College, Chongqing College of Water Resources and Electric Engineering, Yongchuan Chongqing 402160, China
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.
Key words:  mobile phone  immune danger theory  antigen presenting cells  malware detection
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