A Framework for Automatic Detection of Vulnerabilities in Human-Machine Pair Programming

• Item type: Symposium(1)
• 公開日: 2021-08-30
• タイトル: A Framework for Automatic Detection of Vulnerabilities in Human-Machine Pair Programming
• タイトル / 言語: en
• タイトル: A Framework for Automatic Detection of Vulnerabilities in Human-Machine Pair Programming
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 安全性・セキュリティ
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: Hiroshima University
• 著者所属: Hiroshima University
• 著者所属: Hiroshima University
• 著者所属(英): en
• 著者所属(英): Hiroshima University
• 著者所属(英): en
• 著者所属(英): Hiroshima University
• 著者所属(英): en
• 著者所属(英): Hiroshima University
• 著者名: Pingyan, Wang; Shaoying, Liu; Ai, Liu
• 著者名(英): Pingyan, Wang; Shaoying, Liu; Ai, Liu
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In order to mitigate the severe consequences of security threats, many software-based systems are endeavoring to detect security vulnerabilities as early as possible in the software life cycle. In this paper, we present a framework for systematically detecting and mitigating potential security vulnerabilities during the construction of programs using a particular programming paradigm known as Human-Machine Pair Programming. The framework allows developers to address the vulnerability problem in the coding phase rather than fix it at a high price when the system is in operation. Our framework advocates three critical steps: (1) generate an attack tree to model a specific security threat, (2) construct code-matching patterns based on the result of the attack tree analysis, and (3) detect corresponding vulnerable code based on the patterns during the program construction. We also present a case study to demonstrate how it works in practice.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In order to mitigate the severe consequences of security threats, many software-based systems are endeavoring to detect security vulnerabilities as early as possible in the software life cycle. In this paper, we present a framework for systematically detecting and mitigating potential security vulnerabilities during the construction of programs using a particular programming paradigm known as Human-Machine Pair Programming. The framework allows developers to address the vulnerability problem in the coding phase rather than fix it at a high price when the system is in operation. Our framework advocates three critical steps: (1) generate an attack tree to model a specific security threat, (2) construct code-matching patterns based on the result of the attack tree analysis, and (3) detect corresponding vulnerable code based on the patterns during the program construction. We also present a case study to demonstrate how it works in practice.
• 書誌情報: ソフトウェアエンジニアリングシンポジウム2021論文集; 巻 2021, p. 129-136, 発行日 2021-08-30
• 出版者 / 言語: ja
• 出版者: 情報処理学会