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Using secure coprocessors for privacy preserving collaborative data mining and analysis
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Source Data Management On New Hardware archive
Proceedings of the 2nd international workshop on Data management on new hardware table of contents
Chicago, Illinois
SESSION: Data mining, knowledge discovery & OLTP table of contents
Article No. 1  
Year of Publication: 2006
ISBN:1-59593-466-9
Authors
Bishwaranjan Bhattacharjee  IBM T. J. Watson Research Center
Naoki Abe  IBM T. J. Watson Research Center
Kenneth Goldman  IBM T. J. Watson Research Center
Bianca Zadrozny  Universidade Federal Fluminense
Vamsavardhana R. Chillakuru  IBM
Marysabel del Carpio  IBM
Chid Apte  IBM T. J. Watson Research Center
Sponsor
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Secure coprocessors have traditionally been used as a keystone of a security subsystem, eliminating the need to protect the rest of the subsystem with physical security measures. With technological advances and hardware miniaturization they have become increasingly powerful. This opens up the possibility of using them for non traditional use. This paper describes a solution for privacy preserving data sharing and mining using cryptographically secure but resource limited coprocessors. It uses memory light data mining methodologies along with a light weight database engine with federation capability, running on a coprocessor. The data to be shared resides with the enterprises that want to collaborate. This system will allow multiple enterprises, which are generally not allowed to share data, to do so solely for the purpose of detecting particular types of anomalies and for generating alerts. We also present results from experiments which demonstrate the value of such collaborations.


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:
Bishwaranjan Bhattacharjee: colleagues
Naoki Abe: colleagues
Kenneth Goldman: colleagues
Bianca Zadrozny: colleagues
Vamsavardhana R. Chillakuru: colleagues
Marysabel del Carpio: colleagues
Chid Apte: colleagues