Secure statistical databases with random sample queries
نویسندگان
چکیده
منابع مشابه
Microdatadisclosurelimitationin Statistical Databases: Quev Size and Random Sample Qwy Control
A probabilistic framework can be employed to assess the n“skof disclosure of confidential information in statistical databases that use disclosure control mechanisms. We illustrate how the method may be used to assess the strengths and weaknesses of two tm”stingdisclosure control mechanisms quey set size res&”ctioncontrol and random sample query control mechanisms. Our results indicate that nei...
متن کاملAuditing User Queries in Dynamic Statistical Databases
Chin proposed an audit scheme for inference control in statistical databases (SDBs) which can determine whether or not a query will lead to the compromise of an SDB. As Chin points out that the dynamic updates of an SDB are prohibited in this scheme because, otherwise, the time and storage requirements will become infinite. The restriction limits the use of this scheme since many SDBs need to b...
متن کاملSub-linear Queries Statistical Databases: Privacy with Power
We consider a statistical database in which a trusted administrator introduces noise to the query responses with the goal of maintaining privacy of individual database entries. In such a database, a query consists of a pair (S, f) where S is a set of rows in the database and f is a function mapping database rows to {0, 1}. The true response is ∑ r∈S f(DBr), a noisy version of which is released....
متن کاملSecure Statistical Analysis of Distributed Databases
A continuing need in the contexts of homeland security, national defense and counterterrorism is for statistical analyses that “integrate” data stored in multiple, distributed databases. There is some belief, for example, that integration of data from flight schools, airlines, credit card issuers, immigration records and other sources might have prevented the terrorist attacks of September 11, ...
متن کاملLower Bounds on Learning Random Structures with Statistical Queries
We show that random DNF formulas, random log-depth decision trees and random deterministic finite acceptors cannot be weakly learned with a polynomial number of statistical queries with respect to an arbitrary distribution.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACM Transactions on Database Systems
سال: 1980
ISSN: 0362-5915,1557-4644
DOI: 10.1145/320613.320616