面向android手机平台的网络恶意数据流挖掘研究

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数据流,挖掘,恶意,面向,android
面向android手机平台的网络恶意数据流挖掘研究

严磊;邹山花

【期刊名称】科学技术与工程 【年(),期】2016(016)033

【摘 要】由于android手机平台网络中数据流众多,以往研究出的面向android手机平台网络恶意数据流挖掘方法,均无法对网络恶意数据流进行高效、准确挖掘.故提出一种挖掘效率和挖掘准确性均较高的android手机平台网络恶意数据流挖掘方法.网络恶意数据流通常均有自动收发行为,所提方法利用概率分类法和邻近值法对android手机平台网络数据流进行预分类,使具有自动收发行为的网络数据流优先进行网络恶意数据流挖掘,提高挖掘效率和挖掘准确性.该挖掘方法将网络数据流划分成多段行为向量,对具有自动收发行为的网络数据流和不具有自动收发行为网络数据流采取不同精度的挖掘操作,输出网络恶意数据流,存储网络非恶意数据,供下次挖掘使用.经实验验证可知,研究的方法挖掘效率高、挖掘准确性.%Because of the android platform in the network data flow is numerous, ever developed for android mobile phone platform network malicious data stream mining method, the network malicious data flow were not mined accurately and efficiently mining.Therefore a mining and mining efficiency high accuracy of the android mobile platform network malicious data stream mining method were proposed.Network malicious data flow often have automatic transceiver behavior, the proposed method using the method of probability classification and adjacent values for android mobile phone platform network data flow classification, the network data flow


were made, with automatic transceiver behavior priority for network malicious data stream mining, the efficiency of mining and mining accuracy were improved.The mining method will be divided into many segments behavior vector network data flow, with automatic transceiver behavior of the network data flow and do not have automatic transceiver behavior of the network data flow to different precision of the mining operation, the output network malicious data streams, the network of malicious data flow for storage, for the use of mining next time.After the experimental verification shows that the research method of high efficiency mining, mining accuracy is high. 【总页数】5(P79-83) 【作 者】严磊;邹山花

【作者单位】无锡太湖学院工学,无锡 214064;无锡太湖学院工学,无锡 214064

【正文语种】 【中图分类】TP309 【相关文献】

1.面向Android手机平台异常入侵检测的研究 [J], 杨午圣;孙敏 2.面向环境监测的无线传感器网络的数据流挖掘研究 [J], 赵美惠

3.面向动态加载的Android恶意行为动静态检测方法 [J], 郑晓梅; 杨宇飞; 程硕; 潘正东

4.面向Android恶意应用静态检测的特征频数差异增强算法 [J], 李向军;孔珂;


智翔;王科选;肖聚鑫

5.InterDroid:面向概念漂移的可解释性Android恶意软件检测方法 [J], 张炳;;魏筱瑜;任家东

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