Design and security analysis of two robust keyed hash functions based on chaotic neural networks

Abdoun, Nabil; Assad, Safwan El; Déforges, Olivier; Assaf, Rima; Khalil, Mohamad

doi:10.1007/s12652-019-01244-y

Cited by 20 publications

(18 citation statements)

References 68 publications

(71 reference statements)

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“…Finally, we give a comparison of NCpB of the proposed structures with 256-bit and 512-bit hash values with some chaos-based hash functions and with the standards SHA-2 and SHA-3 for one Mbits data size in Table 20 . We observe that the obtained NCpB is better than the NCpB of the other cited works, except for that obtained in our previous work [ 47 ]. It is because the the structure of the Sponge construction is more complex than that of the Merkle–D

mgard construction.…”

Section: Performance Analysiscontrasting

confidence: 83%

“…The proposed keyed-Sponge hash functions are the chaotic functions

that contain a CS and a CNN [ 47 ]. These chaotic functions use a padded message block

of size b -bit, subkeys

of length 128 bits and a secret key

of length

= 160 bits and produce hash values with two variant lengths, 256 bits and 512 bits, depending on the value of r and c as shown in Figure 3 .…”

Section: Proposed Keyed-sponge Chaotic Neural Network Hash Functiomentioning

confidence: 99%

“…In addition, we study the immunity of the proposed structures against the brute-force and cryptanalytic attacks. The detailed description of these tests is presented in our previous work [ 47 ]. For that, we just resume in this section the necessary test description to interpret the obtained results.…”

Section: Performance Analysismentioning

confidence: 99%

“…The digest acts as a kind of signature for the input data. Moreover, when the same hash function H is run for the same input message M , the same hash value h is obtained [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

“…At first, some designers combine both these systems (chaos and neural network) in the Merkle–D

mgard structure to build robust CNN hash functions [ 9 , 10 ]. In our previous work [ 2 ], Abdoun et al. designed, implemented, and analyzed the performance, in terms of security and speed, of two proposed keyed CNN hash functions based on the Merkle–D

mgard (MD) construction with three output schemes, i.e., CNN–Matyas–Meyer–Oseas, Modified CNN–Matyas–Meyer–Oseas, and CNN–Miyaguchi–Preneel.…”

Section: Introductionmentioning

confidence: 99%

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Designing Two Secure Keyed Hash Functions Based on Sponge Construction and the Chaotic Neural Network

Abdoun

Assad

Hoang

et al. 2020

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In this paper, we propose, implement, and analyze the structures of two keyed hashfunctions using the Chaotic Neural Network (CNN). These structures are based on Spongeconstruction, and they produce two variants of hash value lengths, i.e., 256 and 512 bits. The firststructure is composed of two-layered CNN, while the second one is formed by one-layered CNN anda combination of nonlinear functions. Indeed, the proposed structures employ two strong nonlinearsystems, precisely a chaotic system and a neural network system. In addition, the proposed study isa new methodology of combining chaotic neural networks and Sponge construction that is provedsecure against known attacks. The performance of the two proposed structures is analyzed in termsof security and speed. For the security measures, the number of hits of the two proposed structuresdoesn’t exceed 2 for 256-bit hash values and does not exceed 3 for 512-bit hash values. In terms ofspeed, the average number of cycles to hash one data byte (NCpB) is equal to 50.30 for Structure 1,and 21.21 and 24.56 for Structure 2 with 8 and 24 rounds, respectively. In addition, the performance ofthe two proposed structures is compared with that of the standard hash functions SHA-3, SHA-2, andwith other classical chaos-based hash functions in the literature. The results of cryptanalytic analysisand the statistical tests highlight the robustness of the proposed keyed hash functions. It also showsthe suitability of the proposed hash functions for the application such as Message Authentication,Data Integrity, Digital Signature, and Authenticated Encryption with Associated Data.

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mgard construction.…”

Section: Performance Analysiscontrasting

confidence: 83%

“…The proposed keyed-Sponge hash functions are the chaotic functions

that contain a CS and a CNN [ 47 ]. These chaotic functions use a padded message block

of size b -bit, subkeys

of length 128 bits and a secret key

of length

= 160 bits and produce hash values with two variant lengths, 256 bits and 512 bits, depending on the value of r and c as shown in Figure 3 .…”

Section: Proposed Keyed-sponge Chaotic Neural Network Hash Functiomentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

“…The digest acts as a kind of signature for the input data. Moreover, when the same hash function H is run for the same input message M , the same hash value h is obtained [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

“…At first, some designers combine both these systems (chaos and neural network) in the Merkle–D

mgard (MD) construction with three output schemes, i.e., CNN–Matyas–Meyer–Oseas, Modified CNN–Matyas–Meyer–Oseas, and CNN–Miyaguchi–Preneel.…”

Section: Introductionmentioning

confidence: 99%

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