csce522-lect19

csce522-lect19 - Inference Problem Privacy Preserving Data...

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Inference Problem Privacy Preserving Data Mining Lecture 20
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CSCE 522 - Farkas 2 Lecture 19 Readings and Assignments I. Moskowitz, M. H. Kang: Covert Channels – Here to Stay? http://citeseer.nj.nec.com/cache/papers/cs/1340/http:zSzzSzwww.itd.nrl.na Jajodia, Meadows: Inference Problems in Multilevel Secure Database Management Systems http://www.acsac.org/secshelf/book001/book001.html , essay 24
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CSCE 522 - Farkas 3 Lecture 19 Indirect Information Flow Channels Covert channels Inference channels
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CSCE 522 - Farkas 4 Lecture 19 Communication Channels Overt Channel : designed into a system and documented in the user's manual Covert Channel : not documented. Covert channels may be deliberately inserted into a system, but most such channels are accidents of the system design.
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CSCE 522 - Farkas 5 Lecture 19 Covert Channel Timing Channel: based on system times Storage channels: not time related communication Can be turned into each other
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CSCE 522 - Farkas 6 Lecture 19 Inference Channels + Meta-data Sensitive Information Non-sensitive information =
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CSCE 522 - Farkas 7 Lecture 19 Inference Channels Statistical Database Inferences General Purpose Database Inferences
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CSCE 522 - Farkas 8 Lecture 19 Statistical Databases Goal: provide aggregate information about groups of individuals E.g., average grade point of students Security risk: specific information about a particular individual E.g., grade point of student John Smith Meta-data: Working knowledge about the attributes Supplementary knowledge (not stored in database)
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csce522-lect19 - Inference Problem Privacy Preserving Data...

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