Login

Quantitative Information-Flow Tracking for C and Related Languages

Show full item record




Title: Quantitative Information-Flow Tracking for C and Related Languages
Author: McCamant, Stephen; Ernst, Michael D.
Other Contributors: Program Analysis
Advisor: Michael Ernst
Issue Date: 2006-11-17
Abstract: We present a new approach for tracking programs' use of data througharbitrary calculations, to determine how much information about secretinputs is revealed by public outputs. Using a fine-grained dynamicbit-tracking analysis, the technique measures the information revealedduring a particular execution. The technique accounts for indirectflows, e.g. via branches and pointer operations. Two kinds ofuntrusted annotation improve the precision of the analysis. Animplementation of the technique based on dynamic binary translation isdemonstrated on real C, C++, and Objective C programs of up to half amillion lines of code. In case studies, the tool checked multiplesecurity policies, including one that was violated by a previouslyunknown bug.
URI: http://hdl.handle.net/1721.1/34892
Other Identifiers: MIT-CSAIL-TR-2006-076
Series/Report no.: Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
Keywords: Confidentiality, Privacy, Information disclosure, Tainting, Implicit flows, Valgrind, Memcheck, OpenSSH

Files in this item

Files Size Format
MIT-CSAIL-TR-2006-076.pdf 450.6Kb application/pdf

Files in this item

Files Size Format
MIT-CSAIL-TR-2006-076.ps 1.216Mb application/postscript

This item appears in the following Collection(s)

Show full item record

Search DSpace


Advanced Search

Browse

My Account

Links