1. Pseudo-Random Key Stream Generation Algorithm for Encryption Purposes
- Author
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Zongchao Qiao, Safwan El Assad, Ina Taralova, École Centrale de Nantes (ECN), Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Commande (Commande), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN), Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Commande (LS2N - équipe Commande), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Pseudorandom number generator ,Computer science ,business.industry ,Key space ,Chaotic ,Encryption ,Data type ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD] ,Key (cryptography) ,business ,Algorithm ,Stream cipher ,Block cipher - Abstract
For both chaos-based stream ciphers and chaos-based block ciphers, key streams have a crucial influence on their security. A well designed pseudo-chaotic number generator (PCNG) that exhibits both chaotic properties and pseudo-randomness is a good candidate for creating the cryptographic key stream for encryption purposes. PCNGs are based on multiple chaotic maps. Since the majority of the chaotic maps are defined using real numbers, most of the proposed PCNGs use floating-point notations. However, this data type, especially the double-precision notation, has disadvantages of high computation cost and inefficient resource utilization. Also, the quantification errors may undermine the reliability of the produced key stream. To overcome these drawbacks, a key stream generation algorithm using a PCNG scheme is proposed in this paper. The PCNG is based on reformulated skew tent maps over a 32-bit integer field. It not only reduces the resource utilization from the hardware perspective, but also ensures the key stream performance over various operation platforms. Furthermore, the proposed PCNG uses a parameter changeable strategy, which can help to expand the key space, and thus increases the immunity against the brute-force attack. The quality of the key stream produced by the PCNG has been tested in a stream cipher. The analysis and the obtained test results have demonstrated that the proposed PCNG is secure and reliable to generate cryptographic key streams for encryption purposes.
- Published
- 2020
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