The article describes the operating principles and ways of search engines.It also introduces their types,development,existing problems and applying techniques.
风河为Wind River Intelligent Network Platform（风河智能网络平台）推出一项正在申请专利的数据包加速技术,同时增加一个新的用于网络流量流分析的数据平面软件引擎。这个软件平台非常适用于4G/LTE无线应用、防火墙解决方案和数据包...风河为Wind River Intelligent Network Platform（风河智能网络平台）推出一项正在申请专利的数据包加速技术,同时增加一个新的用于网络流量流分析的数据平面软件引擎。这个软件平台非常适用于4G/LTE无线应用、防火墙解决方案和数据包分析等新一代智能网络设备的设计,展开更多
Mobile malware is rapidly increasing and its detection has become a critical issue. In this study, we summarize the common characteristics of this inalicious software on Android platform. We design a detection engine ...Mobile malware is rapidly increasing and its detection has become a critical issue. In this study, we summarize the common characteristics of this inalicious software on Android platform. We design a detection engine consisting of six parts： decompile, grammar parsing, control flow and data flow analysis, safety analysis, and comprehensive evaluation. In the comprehensive evaluation, we obtain a weight vector of 29 evaluation indexes using the analytic hierarchy process. During this process, the detection engine exports a list of suspicious API. On the basis of this list, the evaluation part of the engine performs a compre- hensive evaluation of the hazard assessment of software sample. Finally, hazard classification is given for the software. The false positive rate of our approach for detecting rnalware samples is 4. 7% and normal samples is 7.6%. The experimental results show that the accuracy rate of our approach is almost similar to the method based on virus signatures. Compared with the method based on virus signatures, our approach performs well in detecting unknown malware. This approach is promising for the application of malware detection.展开更多
文摘The article describes the operating principles and ways of search engines.It also introduces their types,development,existing problems and applying techniques.
基金supported by Major National Science and Technology Projects(No.3) under Grant No. 2012ZX03002012
文摘Mobile malware is rapidly increasing and its detection has become a critical issue. In this study, we summarize the common characteristics of this inalicious software on Android platform. We design a detection engine consisting of six parts： decompile, grammar parsing, control flow and data flow analysis, safety analysis, and comprehensive evaluation. In the comprehensive evaluation, we obtain a weight vector of 29 evaluation indexes using the analytic hierarchy process. During this process, the detection engine exports a list of suspicious API. On the basis of this list, the evaluation part of the engine performs a compre- hensive evaluation of the hazard assessment of software sample. Finally, hazard classification is given for the software. The false positive rate of our approach for detecting rnalware samples is 4. 7% and normal samples is 7.6%. The experimental results show that the accuracy rate of our approach is almost similar to the method based on virus signatures. Compared with the method based on virus signatures, our approach performs well in detecting unknown malware. This approach is promising for the application of malware detection.
