针对手机恶意软件检测问题,提出一种手机恶意软件检测的分布式模型(MPMD-DIM),使手机端和分布式检测服务器以及分布式检测服务器之间协同工作,实现快速准确地检测手机恶意软件。模型利用改进的反向选择算法和动态克隆选择算法优化恶意软件检测过程,及时做出免疫响应;通过分布式检测服务器之间的疫苗提取和接种,产生二次免疫应答,加速检测过程。实验表明,该模型可以提高对已知手机恶意软件的检测率,改善对未知和变化的手机恶意软件的检测准确率,实现手机对恶意软件的群体协防。
For the mobile phone malware detection problem, a distributed immune modal for Mobile Phone MalwareDetection(MPMD-DIM)is proposed, which enables collaborative work between mobile phones and distributed detectionservers, to detect mobile phone malwares quickly and accurately. This modal utilizes improved negative selection algorithmand dynamic clonal selection algorithm to optimize detection process, also gives immune response in time; as well as appliesvaccine extracting and inoculating among distributed detection servers, making secondary immune response rapidly toaccelerating detection process. Experiments demonstrate that this modal can advance detection rate of known mobilephone malwares;enhance detection accuracy rate of unknown mobile phone malwares;and implement grouping defenseof mobile phones.