{"title":"识别Android应用程序的威胁模式","authors":"Chia-Mei Chen, G. Lai, Je-Ming Lin","doi":"10.1109/AsiaJCIS.2017.23","DOIUrl":null,"url":null,"abstract":"Mobile devices have become powerful and popular. Most internet applications or services are ported to mobile platforms. Confidential personal information such as credit card and password usually is stored in mobile devices for ubiquitous computing. Therefore, mobile devices become attack target due to financial gain. Mobile applications are published in various market places without or with little verification; hence malicious mobile applications can be deployed in the marketplaces without any difficulty.In this paper, we present a mobile malware detection approach by identifying the threat patterns. The proposed system analyzes the function invocation and the data flow to identify malicious behaviors in Android mobile devices. The experimental results show that the proposed method can efficiently detect malicious mobile applications including unknown malware.","PeriodicalId":108636,"journal":{"name":"2017 12th Asia Joint Conference on Information Security (AsiaJCIS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Identifying Threat Patterns of Android Applications\",\"authors\":\"Chia-Mei Chen, G. Lai, Je-Ming Lin\",\"doi\":\"10.1109/AsiaJCIS.2017.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile devices have become powerful and popular. Most internet applications or services are ported to mobile platforms. Confidential personal information such as credit card and password usually is stored in mobile devices for ubiquitous computing. Therefore, mobile devices become attack target due to financial gain. Mobile applications are published in various market places without or with little verification; hence malicious mobile applications can be deployed in the marketplaces without any difficulty.In this paper, we present a mobile malware detection approach by identifying the threat patterns. The proposed system analyzes the function invocation and the data flow to identify malicious behaviors in Android mobile devices. The experimental results show that the proposed method can efficiently detect malicious mobile applications including unknown malware.\",\"PeriodicalId\":108636,\"journal\":{\"name\":\"2017 12th Asia Joint Conference on Information Security (AsiaJCIS)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 12th Asia Joint Conference on Information Security (AsiaJCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AsiaJCIS.2017.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th Asia Joint Conference on Information Security (AsiaJCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AsiaJCIS.2017.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying Threat Patterns of Android Applications
Mobile devices have become powerful and popular. Most internet applications or services are ported to mobile platforms. Confidential personal information such as credit card and password usually is stored in mobile devices for ubiquitous computing. Therefore, mobile devices become attack target due to financial gain. Mobile applications are published in various market places without or with little verification; hence malicious mobile applications can be deployed in the marketplaces without any difficulty.In this paper, we present a mobile malware detection approach by identifying the threat patterns. The proposed system analyzes the function invocation and the data flow to identify malicious behaviors in Android mobile devices. The experimental results show that the proposed method can efficiently detect malicious mobile applications including unknown malware.