{"title":"基于时间和位置功率的智能手机恶意代码检测技术","authors":"Bryan Dixon, Shivakant Mishra","doi":"10.1109/TrustCom.2013.22","DOIUrl":null,"url":null,"abstract":"There is a growing number of viruses, malware, and other threats designed to gain access to system resources and information stored on smartphones. This paper examines the effectiveness of three techniques for detecting malicious code based on individual power consumption profiles with a focus on time and location. This project used Google's Android platform for testing and data collection. The paper describes the design, implementation, and evaluation of each of these techniques.","PeriodicalId":399462,"journal":{"name":"2014 IEEE 13th International Symposium on Network Computing and Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Time and Location Power Based Malicious Code Detection Techniques for Smartphones\",\"authors\":\"Bryan Dixon, Shivakant Mishra\",\"doi\":\"10.1109/TrustCom.2013.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is a growing number of viruses, malware, and other threats designed to gain access to system resources and information stored on smartphones. This paper examines the effectiveness of three techniques for detecting malicious code based on individual power consumption profiles with a focus on time and location. This project used Google's Android platform for testing and data collection. The paper describes the design, implementation, and evaluation of each of these techniques.\",\"PeriodicalId\":399462,\"journal\":{\"name\":\"2014 IEEE 13th International Symposium on Network Computing and Applications\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 13th International Symposium on Network Computing and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TrustCom.2013.22\",\"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 13th International Symposium on Network Computing and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TrustCom.2013.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time and Location Power Based Malicious Code Detection Techniques for Smartphones
There is a growing number of viruses, malware, and other threats designed to gain access to system resources and information stored on smartphones. This paper examines the effectiveness of three techniques for detecting malicious code based on individual power consumption profiles with a focus on time and location. This project used Google's Android platform for testing and data collection. The paper describes the design, implementation, and evaluation of each of these techniques.