Cryptanalytic Time/Memory/Data Tradeoffs for Stream Ciphers
ASIACRYPT '00 Proceedings of the 6th International Conference on the Theory and Application of Cryptology and Information Security: Advances in Cryptology
Real Time Cryptanalysis of A5/1 on a PC
FSE '00 Proceedings of the 7th International Workshop on Fast Software Encryption
A Time-Memory Tradeoff Using Distinguished Points: New Analysis & FPGA Results
CHES '02 Revised Papers from the 4th International Workshop on Cryptographic Hardware and Embedded Systems
Fast dictionary attacks on passwords using time-space tradeoff
Proceedings of the 12th ACM conference on Computer and communications security
Characterization and Improvement of Time-Memory Trade-Off Based on Perfect Tables
ACM Transactions on Information and System Security (TISSEC)
The cost of false alarms in Hellman and rainbow tradeoffs
Designs, Codes and Cryptography
Rigorous bounds on cryptanalytic time/memory tradeoffs
CRYPTO'06 Proceedings of the 26th annual international conference on Advances in Cryptology
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Cryptanalytic time memory tradeoff algorithms are tools for quickly inverting one-way functions and many consider the rainbow table method to be the most efficient tradeoff algorithm. However, it was recently announced, mostly based on experiments, that the parallelization of the perfect distinguished point tradeoff algorithm brings about an algorithm that is 50% more efficient than the perfect rainbow table method. Motivated by this claim, we provide an accurate theoretic analysis of the parallel version of the non-perfect distinguished point tradeoff algorithm. Performance differences between different tradeoff algorithms are usually not very large, but even these small differences can be crucial in practice. So we take care not to ignore the side effects of false alarms while analyzing the online time complexity of the parallel distinguished point tradeoff algorithm. Our complexity results are used to compare the parallel non-perfect distinguished point tradeoff against the non-perfect rainbow table method. The two algorithms are compared under identical success rate requirements and the pre-computation efforts are taken into account. Contrary to our anticipation, we find that the rainbow table method is superior in typical situations, even though the parallelization did have a positive effect on the efficiency of the distinguished point tradeoff algorithm.