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Display-only file server: a solution against information theft due to insider attack
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Source ACM Workshop On Digital Rights Management archive
Proceedings of the 4th ACM workshop on Digital rights management table of contents
Washington DC, USA
SESSION: Information protection methods table of contents
Pages: 31 - 39  
Year of Publication: 2004
ISBN:1-58113-969-1
Authors
Yang Yu  Stony Brook University, Stony Brook, NY
Tzi-cker Chiueh  Rether Networks Inc., Centereach, NY
Sponsors
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Insider attack is one of the most serious cybersecurity threats to corporate America. Among all insider threats, information theft is considered the most damaging in terms of potential financial loss. Moreover, it is also especially difficult to detect and prevent, because in many cases the attacker has the proper authority to access the stolen information. According to the 2003 CSI/FBI Computer Crime and Security Survey, theft of proprietary information was the single largest category of losses in the 2003 survey totaling $70.1 million or 35% of the total financial loss reported in that survey. In this paper, we describe the design, implementation and evaluation of an industrial-strength solution called <i>Display-Only File Server</i> (DOFS), which can transparently and effectively stop information theft by insiders in most cases, even if the insiders have proper authorities to read/write the protected information. The DOFS architecture ensures that bits of a protected file never leave a DOFS server after the file is checked in and users can still interact with the protected files in the same way as if it is stored locally. Essentially, DOFS decouples "display access" from other types of accesses to a protected file by providing users only the "display image" rather than the bits of the files, and applies the thin-client computing model on existing client-server applications.


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:
Yang Yu: colleagues
Tzi-cker Chiueh: colleagues