A New Version of the Stream Cipher SNOW

Ekdahl, Patrik; Johansson, Thomas

doi:10.1007/3-540-36492-7_5

Cited by 191 publications

(147 citation statements)

References 9 publications

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“…For the purposes of this paper only the details of the LFSR and the FSM are needed. For a complete description of SNOW 2.0 we refer to the paper [3] …”

Section: The Stream Cipher Snow 20mentioning

confidence: 99%

“…SNOW 2.0 was proposed by Ekdahl and Johansson in [3] as a strengthened version of SNOW 1.0, which was a NESSIE candidate. Currently SNOW 2.0 is considered as one of the most efficient stream ciphers.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the traditional methods such as linear complexity and correlation analysis, attacks based on linear cryptanalysis method have been succesfully launched against stream ciphers. One of the reasons why SNOW 1.0 was rejected by the NESSIE project was its vulnerability against a distinguishing attack using linear cryptanalysis [2,3].…”

Section: Introductionmentioning

confidence: 99%

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Improved Linear Distinguishers for SNOW 2.0

Nyberg

Wallén²

2006

Fast Software Encryption

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Abstract. In this paper we present new and more accurate estimates of the biases of the linear approximation of the FSM of the stream cipher SNOW 2.0. Based on improved bias estimates we also find a new linear distinguisher with bias 2 −86.9 that is significantly stronger than the previously found ones by Watanabe et al. (2003) and makes it possible to distinguish the output keystream of SNOW 2.0 of length 2 174 words from a truly random sequence with workload 2 174 . This attack is also stronger than the recent distinguishing attack by Maximov and Johansson (2005). We also investigate the diffusion properties of the MixColumn transformation used in the FSM of SNOW 2.0 and present some evidence why much more efficient distinguishers may not exist.

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“…For the purposes of this paper only the details of the LFSR and the FSM are needed. For a complete description of SNOW 2.0 we refer to the paper [3] …”

Section: The Stream Cipher Snow 20mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improved Linear Distinguishers for SNOW 2.0

Nyberg

Wallén²

2006

Fast Software Encryption

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“…This holds for most recently proposed stream ciphers, e.g. SEAL [RC98], SCREAM [HCCJ02], SNOW [EJ02], BGML [HN00], and for the stream cipher mode of operation of the KASUMI blockcipher used in the third generation mobile system UMTS [Ka00]. As a consequence, stream ciphers are more conveniently modelled as a length increasing pseudo-random function F K : {0, 1} n → {0, 1} nt ; x → F K (x) = (z 1 , z 2 , · · · , z t ) than as a mere pseudo-random numbers generator allowing to derive a pseudorandom sequence (z 1 , z 2 , · · · , z t ) of nt bits from a secret seed K. The advantage of modelling a stream cipher as a length increasing function generator rather than as a numbers generator is that it allows to reflect the security conditions on the dependance of the pseudo-random sequence in the input value, by requiring that F K be a pseudo-random function, indistinguishable from a perfect random function with the same input and output sizes by any reasonable adversary.…”

Section: Introductionmentioning

confidence: 71%

The Security of ”One-Block-to-Many” Modes of Operation

Gilbert

2003

Fast Software Encryption

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Abstract. In this paper, we investigate the security, in the Luby-Rackoff security paradigm, of blockcipher modes of operation allowing to expand a one-block input into a longer t-block output under the control of a secret key K. Such "one-block-to-many" modes of operation are of frequent use in cryptology. They can be used for stream cipher encryption purposes, and for authentication and key distribution purposes in contexts such as mobile communications. We show that although the expansion functions resulting from modes of operation of blockciphers such as the counter mode or the output feedback mode are not pseudorandom, slight modifications of these two modes provide pseudorandom expansion functions. The main result of this paper is a detailed proof, in the Luby-Rackoff security model, that the expansion function used in the construction of the third generation mobile (UMTS) example authentication and key agreement algorithm MILENAGE is pseudorandom.

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“…[20]. We give a brief description of Snow 2.0; see [11] for details. Snow 2.0 stream cipher is based on one linear feedback shift register made of 16 elements from GF (2 32 ) (that can also be seen as a binary LFSR with 512 bits), and a finite state machine composed of 2 states of 32 bits each, nonlinearly clocked.…”

Section: Elimlin In Cryptanalysis Of Kgsnow 20mentioning

confidence: 99%

Algebraic Description and Simultaneous Linear Approximations of Addition in Snow 2.0.

Courtois

Debraize

2008

Information and Communications Security

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Abstract. In this paper we analyse the algebraic properties over the field GF(2) of the addition modulo 2 n . We look at implicit quadratic equations describing this operation, and at probabilistic conditional linear equations. We show that the addition modulo 2 n can be partly or totally linearized when the output is fixed, and this for a large family of outputs. We apply these results to analyse the resistance of the stream cipher Snow 2.0 against algebraic attacks.

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A New Version of the Stream Cipher SNOW

Cited by 191 publications

References 9 publications

Improved Linear Distinguishers for SNOW 2.0

Improved Linear Distinguishers for SNOW 2.0

The Security of ”One-Block-to-Many” Modes of Operation

Algebraic Description and Simultaneous Linear Approximations of Addition in Snow 2.0.

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