{"title":"A comprehensive framework for inter-app ICC security analysis of Android apps","authors":"Atefeh Nirumand, Bahman Zamani, Behrouz Tork Ladani","doi":"10.1007/s10515-024-00439-8","DOIUrl":null,"url":null,"abstract":"<div><p>The Inter-Component Communication (ICC) model in Android enables the sharing of data and services among app components. However, it has been associated with several problems, including complexity, support for unconstrained communication, and difficulties for developers to understand. These issues have led to numerous security vulnerabilities in Android ICC. While existing research has focused on specific subsets of these vulnerabilities, it lacks comprehensive and scalable modeling of app specifications and interactions, which limits the precision of analysis. To tackle these problems, we introduce VAnDroid3, a Model-Driven Reverse Engineering (MDRE) framework. VAnDroid3 utilizes purposeful model-based representations to enhance the comprehension of apps and their interactions. We have made significant extensions to our previous work, which include the identification of six prominent ICC vulnerabilities and the consideration of both Intent and Data sharing mechanisms that facilitate ICCs. By employing MDRE techniques to create more efficient and accurate domain-specific models from apps, VAnDroid3 enables the analysis of ICC vulnerabilities on intra- and inter-app communication levels. We have implemented VAnDroid3 as an Eclipse-based tool and conducted extensive experiments to evaluate its correctness, scalability, and run-time performance. Additionally, we compared VAnDroid3 with state-of-the-art tools. The results substantiate VAnDroid3 as a promising framework for revealing Android inter-app ICC security issues.</p></div>","PeriodicalId":55414,"journal":{"name":"Automated Software Engineering","volume":"31 2","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automated Software Engineering","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10515-024-00439-8","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
The Inter-Component Communication (ICC) model in Android enables the sharing of data and services among app components. However, it has been associated with several problems, including complexity, support for unconstrained communication, and difficulties for developers to understand. These issues have led to numerous security vulnerabilities in Android ICC. While existing research has focused on specific subsets of these vulnerabilities, it lacks comprehensive and scalable modeling of app specifications and interactions, which limits the precision of analysis. To tackle these problems, we introduce VAnDroid3, a Model-Driven Reverse Engineering (MDRE) framework. VAnDroid3 utilizes purposeful model-based representations to enhance the comprehension of apps and their interactions. We have made significant extensions to our previous work, which include the identification of six prominent ICC vulnerabilities and the consideration of both Intent and Data sharing mechanisms that facilitate ICCs. By employing MDRE techniques to create more efficient and accurate domain-specific models from apps, VAnDroid3 enables the analysis of ICC vulnerabilities on intra- and inter-app communication levels. We have implemented VAnDroid3 as an Eclipse-based tool and conducted extensive experiments to evaluate its correctness, scalability, and run-time performance. Additionally, we compared VAnDroid3 with state-of-the-art tools. The results substantiate VAnDroid3 as a promising framework for revealing Android inter-app ICC security issues.
期刊介绍:
This journal details research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modeling software artifacts and processes.
Coverage in Automated Software Engineering examines both automatic systems and collaborative systems as well as computational models of human software engineering activities. In addition, it presents knowledge representations and artificial intelligence techniques applicable to automated software engineering, and formal techniques that support or provide theoretical foundations. The journal also includes reviews of books, software, conferences and workshops.