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  • 标题:Cross-Programming Language Taint Analysis for the IoT Ecosystem
  • 本地全文:下载
  • 作者:Pietro Ferrara ; Amit Kr Mandal ; Agostino Cortesi
  • 期刊名称:Electronic Communications of the EASST
  • 电子版ISSN:1863-2122
  • 出版年度:2019
  • 卷号:77
  • 页码:1-9
  • DOI:10.14279/tuj.eceasst.77.1104
  • 出版社:European Association of Software Science and Technology (EASST)
  • 摘要:The Internet of Things (IoT) is a key component for the next disruptive technologies. However, IoT merges together several diverse software layers: embedded, enterprise, and cloud programs interact with each other. In addition, security and privacy vulnerabilities of IoT software might be particularly dangerous due to the pervasiveness and physical nature of these systems. During the last decades, static analysis, and in particular taint analysis, has been widely applied to detect software vulnerabilities. Unfortunately, these analyses assume that software is entirely written in a single programming language, and they are not immediately suitable to detect IoT vulnerabilities where many different software components, written in different programming languages, interact. This paper discusses how to leverage existing static taint analyses to a cross-programming language scenario.
  • 关键词:Static Analysis; Taint Analysis; CyberSecurity
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