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.
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.
作者
邹劲松
ZOU Jin-song(Putian Big Data Industrial College,Chongqing College of Water Resources and Electric Engineering,Yongchuan Chongqing 402160,China)
出处
《西南师范大学学报（自然科学版）》
CAS
北大核心
2018年第11期78-85,共8页
Journal of Southwest China Normal University(Natural Science Edition)
