H. Shahriar, K. Qian, Md Arabin Islam Talukder, D. Lo, Nidhibahen Patel
{"title":"动态分析的移动软件安全","authors":"H. Shahriar, K. Qian, Md Arabin Islam Talukder, D. Lo, Nidhibahen Patel","doi":"10.1109/PRDC.2018.00039","DOIUrl":null,"url":null,"abstract":"The majority of malicious mobile attacks take advantage of vulnerabilities in mobile software (applications), such as sensitive data leakage, unsecured sensitive data storage, data transmission, and many others. Most of these vulnerabilities can be detected by analyzing the mobile software. In this paper, we describe a tainted dataflow approach to detect mobile software security vulnerability, particularly, SQL Injection.","PeriodicalId":409301,"journal":{"name":"2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mobile Software Security with Dynamic Analysis\",\"authors\":\"H. Shahriar, K. Qian, Md Arabin Islam Talukder, D. Lo, Nidhibahen Patel\",\"doi\":\"10.1109/PRDC.2018.00039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The majority of malicious mobile attacks take advantage of vulnerabilities in mobile software (applications), such as sensitive data leakage, unsecured sensitive data storage, data transmission, and many others. Most of these vulnerabilities can be detected by analyzing the mobile software. In this paper, we describe a tainted dataflow approach to detect mobile software security vulnerability, particularly, SQL Injection.\",\"PeriodicalId\":409301,\"journal\":{\"name\":\"2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRDC.2018.00039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRDC.2018.00039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The majority of malicious mobile attacks take advantage of vulnerabilities in mobile software (applications), such as sensitive data leakage, unsecured sensitive data storage, data transmission, and many others. Most of these vulnerabilities can be detected by analyzing the mobile software. In this paper, we describe a tainted dataflow approach to detect mobile software security vulnerability, particularly, SQL Injection.