{"title":"手机恶意软件暴露","authors":"Alaa Salman, I. Elhajj, A. Chehab, A. Kayssi","doi":"10.1109/AICCSA.2014.7073206","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new method to detect malicious activities on mobile devices by examining an application's runtime behavior. To this end, we use the Xposed framework to build a monitoring module that generates behavior profiles for applications. The module integrates with our intrusion detection system which then analyzes and reports on the profiles. We use this tool to detect malicious behavior patterns using both a custom-written malware and a real one. We also detect behavior patterns for some popular applications from the Google Play Store to expose their functionality. The results show that standard techniques that are used to evade static analysis are not effective against our monitoring approach. This approach can also be generalized to detect unknown malware or expose exact application behavior to the user.","PeriodicalId":412749,"journal":{"name":"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mobile malware exposed\",\"authors\":\"Alaa Salman, I. Elhajj, A. Chehab, A. Kayssi\",\"doi\":\"10.1109/AICCSA.2014.7073206\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new method to detect malicious activities on mobile devices by examining an application's runtime behavior. To this end, we use the Xposed framework to build a monitoring module that generates behavior profiles for applications. The module integrates with our intrusion detection system which then analyzes and reports on the profiles. We use this tool to detect malicious behavior patterns using both a custom-written malware and a real one. We also detect behavior patterns for some popular applications from the Google Play Store to expose their functionality. The results show that standard techniques that are used to evade static analysis are not effective against our monitoring approach. This approach can also be generalized to detect unknown malware or expose exact application behavior to the user.\",\"PeriodicalId\":412749,\"journal\":{\"name\":\"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICCSA.2014.7073206\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2014.7073206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a new method to detect malicious activities on mobile devices by examining an application's runtime behavior. To this end, we use the Xposed framework to build a monitoring module that generates behavior profiles for applications. The module integrates with our intrusion detection system which then analyzes and reports on the profiles. We use this tool to detect malicious behavior patterns using both a custom-written malware and a real one. We also detect behavior patterns for some popular applications from the Google Play Store to expose their functionality. The results show that standard techniques that are used to evade static analysis are not effective against our monitoring approach. This approach can also be generalized to detect unknown malware or expose exact application behavior to the user.