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2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(ICIS2009)

作者： Huihui Zhao Jianxin Chen Beijing University of Chinese Medicine Beijing 100029 China Qin Hou Beijing Document Service Beijing 100036 China Na Hou Beijing Hospital of Traditional Chinese Medicine Beijing 100010 China Jing Han Peng Zhang Yong Wang Wei Wang Beijing University of Chinese Medicine Beijing 100029 China

Coronary heart disease is now a severe burden on society and family in both industrialized and developing countries,but the traditional related factors can not explain the whole situations.The effect of treatment is very limited.Determination of treatment based on the symptoms and signs in Traditional Chinese Medicine （TCM） have certain curative effect.But the objective of the syndrome diagnose is a very urgent and difficult problem in TCM.Under the foundation work we had done,the aim of this study was to search for a novel feature selection method for the chose of protein biomarkers for unstable angina （UA） with blood stasis syndrome.Plasma samples were obtained from twenty-four unstable angina patients and twelve healthy volunteers.A polyclonal antibody affinity column was used to remove the six most abundant proteins.Then,the two classes of samples were separated by Two-dimensional difference gel electrophoresis （2D-DIGE）.The differentially expressed protein spots were selected and identified with matrix-assisted laser desorption /ionization time-of-flight mass spectrometry （MALDI-TOF-MS） or MS-MS.Using multi-layer perceptron,we choose the protein biomarkers for UA with blood stasis syndrome.By using a back elimination method integrated with classification methods,it is found that the optimal number of proteins is six,i.e.,α1-Antitrypsin 2,HP cleaved β,α1-Antitrypsin,ApoA-I,DBP4,Fg β 2.The proteins are biomarkers to separate UA with blood stasis syndrome from health control.The UA with blood stasis syndrome diagnosis accuracy could reach 96 %.The obtained patterns are validated by 3-fold cross validation.The multi-layer perceptron may be a useful novel feature selection method for the choosing of protein biomarkers for CHD.

关键词： Multi-layer perceptron feature selection method Coronary heart disease Unstable angina Blood stasis syndrome Traditional Chinese Medicine biomarker

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Android Malware Detection method Based on Permission Complement and API Calls

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Chinese Journal of Electronics 2022年第4期31卷 773-785页

作者： YANG Jiyun TANG Jiang YAN Ran XIANG Tao College of Computer Science Chongqing University

The dynamic code loading mechanism of the Android system allows an application to load executable files externally at runtime. This mechanism makes the development of applications more convenient, but it also brings security issues. Applications that hide malicious behavior in the external file by dynamic code loading are becoming a new challenge for Android malware detection. To overcome this challenge, based on dynamic code loading mechanisms, three types of threat models,i.e. Model I, Model II, and Model III are defined. For the Model I type malware, its malicious behavior occurs in Dex Code, so the application programming interface(API)classes were used to characterize the behavior of the DexCode file. For the Model II type and Model III type malwares whose malicious behaviors occur in an external file,the permission complement is defined to characterize the behaviors of the external file. Based on permission complement and API calls, an Android malicious application detection method is proposed, of which feature sets are constructed by improving a feature selection method. Five datasets containing 15,581 samples are used to evaluate the performance of the proposed method. The experimental results show that our detection method achieves accuracy of 99.885% on general dataset, and performes the best on all evaluation metrics on all datasets in all comparison methods.

关键词： Android malicious application detection method threat models API calls Data security malicious behavior Android malware detection method Operating systems DexCode file executable files application programming interface classes Android (operating system) Ubiquitous and pervasive computing permission complement invasive software external file dynamic code loading mechanism application program interfaces feature selection method feature selection

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