Trace Wringing for Program Trace Privacy

A quantitative approach to optimizing computer systems requires a good understanding of how applications exercise a machine, and real program traces from production environments lead to the clearest understanding. Unfortunately, even the simplest program traces can leak sensitive details about users...

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Bibliographic Details
Published inIEEE MICRO Vol. 40; no. 3; pp. 108 - 115
Main Authors Dangwal, Deeksha, Cui, Weilong, McMahan, Joseph, Sherwood, Timothy
Format Journal Article
LanguageEnglish
Published Los Alamitos IEEE 01.05.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Computer simulation
Encryption
Optimization
Privacy
Probabilistic logic
Security
Signal processing
Space heating
Transforms
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Summary:A quantitative approach to optimizing computer systems requires a good understanding of how applications exercise a machine, and real program traces from production environments lead to the clearest understanding. Unfortunately, even the simplest program traces can leak sensitive details about users, their recent activity, or even details of trade secret algorithms. Given the cleverness of attackers working to undo well-intentioned, but ultimately insufficient, anonymization techniques, many organizations have simply decided to cease making traces available. Trace wringing is a new formulation of the problem of sharing traces where one knows a priori how much information the trace is leaking in the worst case. The key idea is to squeeze as much information as possible out of the trace without completely compromising its usefulness for optimization. We demonstrate the utility of a wrung trace through cache simulation and examine the sensitivity of wrung traces to a class of attacks on Advanced Encryption Standard (AES) encryption.
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2020.2986113