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Privacy oracle: a system for finding application leaks with black box differential testing
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Conference on Computer and Communications Security archive
Proceedings of the 15th ACM conference on Computer and communications security table of contents
Alexandria, Virginia, USA
SESSION: Privacy 2 table of contents
Pages 279-288  
Year of Publication: 2008
ISBN:978-1-59593-810-7
Authors
Jaeyeon Jung  Intel Research, Seattle, WA, USA
Anmol Sheth  Intel Research, Seattle, WA, USA
Ben Greenstein  Intel Research, Seattle, WA, USA
David Wetherall  Intel Research, Seattle, WA, USA
Gabriel Maganis  University of Washington, Seattle, WA, USA
Tadayoshi Kohno  University of Washington, Seattle, WA, USA
Sponsors
ACM: Association for Computing Machinery
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
Publisher
ACM  New York, NY, USA
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ABSTRACT

We describe the design and implementation of Privacy Oracle, a system that reports on application leaks of user information via the network traffic that they send. Privacy Oracle treats each application as a black box, without access to either its internal structure or communication protocols. This means that it can be used over a broad range of applications and information leaks (i.e., not only Web traffic or credit card numbers). To accomplish this, we develop a differential testing technique in which perturbations in the application inputs are mapped to perturbations in the application outputs to discover likely leaks; we leverage alignment algorithms from computational biology to find high quality mappings between different byte-sequences efficiently. Privacy Oracle includes this technique and a virtual machine-based testing system. To evaluate it, we tested 26 popular applications, including system and file utilities, media players, and IM clients. We found that Privacy Oracle discovered many small and previously undisclosed information leaks. In several cases, these are leaks of directly identifying information that are regularly sent in the clear (without end-to-end encryption) and which could make users vulnerable to tracking by third parties or providers.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Jaeyeon Jung: colleagues
Anmol Sheth: colleagues
Ben Greenstein: colleagues
David Wetherall: colleagues
Gabriel Maganis: colleagues
Tadayoshi Kohno: colleagues