## Abstract

The first part of this chapter discusses recently proposed quasigroup-based block cipher with applications in low-powered computationally constrained environments. We present some preliminary analysis of the block cipher using NIST Statistical Analysis Tool (second half discusses the linear cryptanalysis). We also present our results on hardware implementation of quasigroup-based block cipher. In the second part of the chapter, we determine whether any key material can be found by conducting a linear cryptanalysis of the cipher matrix lookup transformations on the input blocks using the key bytes. Linear cryptanalysis involves a known-plaintext attack such that a set of plaintexts is known to have a specific statistical relationship to a set of ciphertexts which are all encrypted under the same key. Using Matsui's Algorithm 2 for DES S-box transformations as an example, we seek to determine a suitable linear approximation of the quasigroup block cipher, the number of plaintext-ciphertext pairs to test, and the amount of time and space required to mount a known-plaintext attack on the quasigroup block cipher. Our research showed that no key material could be recovered, and therefore, we conclude that the quasigroup cipher is resistant to linear cryptanalysis. Since the quasigroup does not use a Feistel network with S-box transformations as the basis of encryption, the focus of the linear cryptanalysis was on the keyed transformation during table lookups of the quasigroup, in order to 1) determine how the key bits used during encryption impact the ciphertext, and from this 2) find a linear approximation that is non-negligible.

Original language | English (US) |
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Title of host publication | Security, Privacy and Reliability in Computer Communications and Networks |

Publisher | River Publishers |

Pages | 177-204 |

Number of pages | 28 |

ISBN (Electronic) | 9788793379909 |

ISBN (Print) | 9788793379893 |

State | Published - Feb 1 2017 |

## Keywords

- Low-energy encryption
- Quasigroup encryption
- Resource constrained algorithm

## ASJC Scopus subject areas

- Computer Science(all)
- Engineering(all)