The knowledge complexity of interactive proof-systems
STOC '85 Proceedings of the seventeenth annual ACM symposium on Theory of computing
Winnowing: local algorithms for document fingerprinting
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Private collaborative forecasting and benchmarking
Proceedings of the 2004 ACM workshop on Privacy in the electronic society
Similar Document Detection with Limited Information Disclosure
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
Efficient privacy-preserving similar document detection
The VLDB Journal — The International Journal on Very Large Data Bases
On private scalar product computation for privacy-preserving data mining
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
EsPRESSO: Efficient privacy-preserving evaluation of sample set similarity
Journal of Computer Security
| Hi-index | 0.00 |
Secure similar document detection (SSDD) plays an important role in many applications, such as justifying the need-to-know basis and facilitating communication between government agencies. The SSDD problem considers situations where Alice with a query document wants to find similar information from Bob's document collection. During this process, the content of the query document is not disclosed to Bob, and Bob's document collection is not disclosed to Alice. Existing SSDD protocols are developed under the vector space model, which has the advantage of identifying global similar information. To effectively and securely detect similar documents with overlapping text fragments, this paper proposes a novel n-gram based SSDD protocol.