Is the Data Encryption Standard a Group? (Preliminary Abstract)

7Citations
Citations of this article
29Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The Data Encryption Standard (DES) defines an indexed set of permutations acting on the message space M = {0,1}64. If this set of permutations were closed under functional composition, then DES would be vulnerable to a known-plaintext attack that runs in 228 steps, on the average. It is unknown in the open literature whether or not DES has this weakness. We describe two statistical tests for determining if an indexed set of permutations acting on a finite message space forms a group under functional composition. The first test is a “meet-in-the-middle” algorithm which uses O(√K) time and space, where K is the size of the key space. The second test, a novel cycling algorithm, uses the same amount of time but only a small constant amount of space. Each test yields a known-plaintext attack against any finite, deterministic cryptosystem that generates a small group. The cycling test takes a pseudo-random walk in the message space until a cycle is detected. For each step of the pseudo-random walk, the previous ciphertext is encrypted under a key chosen by a pseudo-random function of the previous ciphertext. Results of the test are asymmetrical: long cycles are overwhelming evidence that the set of permutations is not a group; short cycles are strong evidence that the set of permutations has a structure different from that expected from a set of randomly chosen permutations. Using a combination of software and special-purpose hardware, we applied the cycling test to DES. Our experiments show, with a high degree of confidence, that DES is not a group.

Cite

CITATION STYLE

APA

Kaliski, B. S., Rivest, R. L., & Sherman, A. T. (1986). Is the Data Encryption Standard a Group? (Preliminary Abstract). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 219 LNCS, pp. 81–95). Springer Verlag. https://doi.org/10.1007/3-540-39805-8_10

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free