@inproceedings{f0c816e50caa4b7d9cee494a65e40be2,
title = "Towards a Flow- and Path-Sensitive Information Flow Analysis",
abstract = "This paper investigates a flow- and path-sensitive static information flow analysis. Compared with security type systems with fixed labels, it has been shown that flow-sensitive type systems accept more secure programs. We show that an information flow analysis with fixed labels can be both flow- and path-sensitive. The novel analysis has two major components: 1) a general-purpose program transformation that removes false dataflow dependencies in a program that confuse a fixed-label type system, and 2) a fixed-label type system that allows security types to depend on path conditions. We formally prove that the proposed analysis enforces a rigorous security property: noninterference. Moreover, we show that the analysis is strictly more precise than a classic flow-sensitive type system, and it allows sound control of information flow in the presence of mutable variables without resorting to run-time mechanisms.",
author = "Peixuan Li and Danfeng Zhang",
note = "Funding Information: We thank our shepherd Nataliia Bielova and anonymous reviewers for their helpful suggestions. The noninterference proof in the full version of this paper [30] is based on a note by Andrew Myers. This work was supported by NSF grant CCF-1566411.; 30th IEEE Computer Security Foundations Symposium, CSF 2017 ; Conference date: 21-08-2017 Through 25-08-2017",
year = "2017",
month = sep,
day = "25",
doi = "10.1109/CSF.2017.17",
language = "English (US)",
series = "Proceedings - IEEE Computer Security Foundations Symposium",
publisher = "IEEE Computer Society",
pages = "53--67",
booktitle = "Proceedings - IEEE 30th Computer Security Foundations Symposium, CSF 2017",
address = "United States",
}