Security without identification: transaction systems to make big brother obsolete
Communications of the ACM
Efficient dispersal of information for security, load balancing, and fault tolerance
Journal of the ACM (JACM)
Distributed fingerprints and secure information dispersal
PODC '93 Proceedings of the twelfth annual ACM symposium on Principles of distributed computing
A Pseudorandom Generator from any One-way Function
SIAM Journal on Computing
Untraceable electronic mail, return addresses, and digital pseudonyms
Communications of the ACM
Communications of the ACM
Customer Retention via Data Mining
Artificial Intelligence Review - Issues on the application of data mining
DRG-cache: a data retention gated-ground cache for low power
Proceedings of the 39th annual Design Automation Conference
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Generalized Secret Sharing and Monotone Functions
CRYPTO '88 Proceedings of the 8th Annual International Cryptology Conference on Advances in Cryptology
Time-lock Puzzles and Timed-release Crypto
Time-lock Puzzles and Timed-release Crypto
How to generate cryptographically strong sequences of pseudo random bits
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Theory and application of trapdoor functions
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
DSOM'05 Proceedings of the 16th IFIP/IEEE Ambient Networks international conference on Distributed Systems: operations and Management
| Hi-index | 0.00 |
The retention of communication data has recently attracted much public interest, mostly because of the possibility of its misuse. In this paper, we present protocols that address the privacy concerns of the communication partners. Our data retention protocols store streams of encrypted data items, some of which may be flagged as critical (representing misbehavior). The frequent occurrence of critical data items justifies the self-decryption of all recently stored data items, critical or not. Our first protocol allows the party gathering the retained data to decrypt all data items collected within, say, the last half year whenever the number of critical data items reaches some threshold within, say, the last month. The protocol ensures that the senders of data remain anonymous but may reveal that different critical data items came from the same sender. Our second, computationally more complex scheme obscures this affiliation of critical data with high probability.