面向Android手机平台异常入侵检测的研究

Research on Android mobile phone platform for anomaly intrusion detection

智能手机应用普及的同时,入侵的危害也越来越严重。针对Android智能手机平台,结合入侵检测的相关研究,解决智能手机入侵检测的问题。采取在Android平台下采集系统和网络特征数据,上传至远程云服务器,在服务器上利用SVM进行分析处理,以给出合理的入侵与否的判断,进而尽快更新手机的处理机制。实验结果表明,既减少了智能手机资源消耗,又能对手机的异常入侵尽快做出反应和处理。

With the popularity of smart mobile phone, the harm of intrusion is more and more serious. This paper is, based on the Android smartphone platform, combined with intrusion detection research, to solve the problem of intrusion detection of smartphone. In order to give a reasonable judgment and update the phone as soon as possible, the paper collects the system and the network characteristic data on the Android platform, and uploads them to the remote cloud servers, then analyzes using Support Vector Machine（SVM）. The experimental results show that, taking the kind of mechanism not only can reduce resource consumption of smart phones, but also can handle and response the intrusion as quickly as possible.