https://www.mdu.se/

Information flow control aims at detecting the flow of sensitive information during the program execution in order to ensure the confidentiality and integrity of secret data. Static program dependency analysis calculates data and control dependencies that can be used to detect leakage of secret information. However, secret information can also be leaked through the timing channel inherent in the structure of the code, which cannot be identified using only the data and control dependencies. In this paper, we introduce the concept of Time-Sensitive Control Closure (TSCC), which offers a very general notion of control dependency. We demonstrate the application of TSCC to the fundamental semantic notion of secure information flow called noninterference. By combining TSCC with data dependencies, we develop program slicing techniques capable of detecting security leaks through both information and timing channels. To compute TSCC efficiently, we present a log-linear time algorithm to generate the influencer graph representation of programs, and a linear time algorithm to compute TSCC from the generated influencer graph. Our algorithm is implemented within the Clang/LLVM compiler infrastructure, and we conduct experiments using well-known benchmarks. The experimental evaluation validates the accuracy and performance improvements offered by the TSCC algorithm compared to existing control dependency approaches. These results demonstrate the practical utility of TSCC in enhancing the security of real-world applications.