Take the 2-minute tour ×
Cryptography Stack Exchange is a question and answer site for software developers, mathematicians and others interested in cryptography. It's 100% free, no registration required.

Obviously, much of cryptography requires the assumption that adversaries have bounded computing power.

So, I was wondering, are there any fields in cryptographic research for which high power computing would aid researchers? Obviously, even the most advanced computers today will not give them an asymptotic advantage, but my question is:

Does crypto research require high computing power and if so specifically which field?

share|improve this question

2 Answers 2

up vote 3 down vote accepted

Insofar as cryptanalysis is considered a part of crypto research, certainly. More computing power is always helpful for breaking ciphers, and indeed, some of the more notable massive distributed computing efforts of recent decades have involved the brute force breaking of cipher challenges such as the RSA Factoring, DES and Secret-Key Challenges. Even with more "analytical" attacks, such as the recent MD5 collision attacks, the final stage of the attack typically still requires testing a large number of candidate values by brute force, a task made considerably easier by the availability of high computing power.

In other parts of crypto research, not so much, although some recent crypto primitives have made use of computationally intensive (pseudo-) Monte Carlo methods for choosing constants or combinations of operations to maximize desired cryptographic properties. For example, the rotation constants of the Threefish block cipher used in the SHA-3 finalist hash function Skein were selected using a genetic algorithm.

share|improve this answer

Most cryptography research does not require high computing power.

For example, doing cryptanalysis of a cipher to actually recover the key with some attack might require a lot of computing power. However, that's not research. Usually discovering the attack method in the first place (which is the research part) does not require a lot of computing power -- instead, it requires a lot of smarts, hard work, and maybe some inspiration.

share|improve this answer

Your Answer

 
discard

By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.