Implementing Erasure Policies Using Taint Analysis
Implementing Erasure Policies Using Taint Analysis
复制标题
使用污点分析实施擦除策略
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
David Sands
中科院分区：
文献类型：
--
作者：
F. Tedesco;Alejandro Russo;David Sands
安全或隐私关键型应用程序通常需要访问敏感信息才能正常运行。但是，根据最小特权原则-或者可能仅仅是为了遵守法律的-一旦信息达到其目的，这些应用程序就不应保留上述信息。在这种情况下，及时处置数据被称为信息擦除策略。本文研究了程序操作数据的软件级信息擦除策略。本文提出了一种新的方法来执行这些政策。我们采用动态污点分析的思想来跟踪敏感数据源如何通过程序传播，并按需删除它们。该方法是作为一个库为Python实现的，没有对运行时系统进行修改。该库易于使用，并且允许程序员仅对代码进行微小修改即可指示信息擦除策略。
Security or privacy-critical applications often require access to sensitive information in order to function. But in accordance with the principle of least privilege --- or perhaps simply for legal compliance --- such applications should not retain said information once it has served its purpose. In such scenarios, the timely disposal of data is known as an information erasure policy . This paper studies software-level information erasure policies for the data manipulated by programs. The paper presents a new approach to the enforcement of such policies. We adapt ideas from dynamic taint analysis to track how sensitive data sources propagate through a program and erase them on demand. The method is implemented for Python as a library, with no modifications to the runtime system. The library is easy to use, and allows programmers to indicate information-erasure policies with only minor modifications to their code.