Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
An algorithm for linear programming which requires O((m+n)n2 + (m+n)1.5n)L) arithmetic operations
Mathematical Programming: Series A and B
Highly resilient correctors for polynomials
Information Processing Letters
Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Introduction to Algorithms
Statistical Databases: Characteristics, Problems, and some Solutions
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Practical privacy: the SuLQ framework
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ACM SIGKDD Explorations Newsletter
Smooth sensitivity and sampling in private data analysis
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
The price of privacy and the limits of LP decoding
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Privacy, accuracy, and consistency too: a holistic solution to contingency table release
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Mechanism Design via Differential Privacy
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
A learning theory approach to non-interactive database privacy
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Ask a better question, get a better answer a new approach to private data analysis
ICDT'07 Proceedings of the 11th international conference on Database Theory
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Toward privacy in public databases
TCC'05 Proceedings of the Second international conference on Theory of Cryptography
Our data, ourselves: privacy via distributed noise generation
EUROCRYPT'06 Proceedings of the 24th annual international conference on The Theory and Applications of Cryptographic Techniques
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
The Differential Privacy Frontier (Extended Abstract)
TCC '09 Proceedings of the 6th Theory of Cryptography Conference on Theory of Cryptography
Differential privacy in new settings
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Private and continual release of statistics
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming: Part II
Differential privacy and the fat-shattering dimension of linear queries
APPROX/RANDOM'10 Proceedings of the 13th international conference on Approximation, and 14 the International conference on Randomization, and combinatorial optimization: algorithms and techniques
Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
Private and Continual Release of Statistics
ACM Transactions on Information and System Security (TISSEC)
Proceedings of the 4th ACM workshop on Security and artificial intelligence
SIAM Journal on Computing
Distributed privacy-preserving methods for statistical disclosure control
DPM'09/SETOP'09 Proceedings of the 4th international workshop, and Second international conference on Data Privacy Management and Autonomous Spontaneous Security
The power of the dinur-nissim algorithm: breaking privacy of statistical and graph databases
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
Unconditional differentially private mechanisms for linear queries
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Optimal private halfspace counting via discrepancy
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security
Security of random output perturbation for statistical databases
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
Non-interactive differential privacy: a survey
Proceedings of the First International Workshop on Open Data
Theoretical Results on De-Anonymization via Linkage Attacks
Transactions on Data Privacy
A learning theory approach to noninteractive database privacy
Journal of the ACM (JACM)
The geometry of differential privacy: the sparse and approximate cases
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
Mechanism design in large games: incentives and privacy
Proceedings of the 5th conference on Innovations in theoretical computer science
Journal of Computer Security
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The goal of a statistical database is to provide statistics about a population while simultaneously protecting the privacy of the individual records in the database. The tension between privacy and usability of statistical databases has attracted much attention in statistics, theoretical computer science, security, and database communities in recent years. A line of research initiated by Dinur and Nissim investigates for a particular type of queries, lower bounds on the distortion needed in order to prevent gross violations of privacy. The first result in the current paper simplifies and sharpens the Dinur and Nissim result.The Dinur-Nissim style results are strong because they demonstrate insecurity of all low-distortion privacy mechanisms. The attacks have an all-or-nothing flavor: letting ndenote the size of the database, 茂戮驴(n) queries are made before anything is learned, at which point 茂戮驴(n) secret bits are revealed. Restricting attention to a wide and realistic subset of possible low-distortion mechanisms, our second result is a more acute attack, requiring only a fixed number of queries for each bit revealed.