Beyond Statistical Analysis in Chaos‐Based CSPRNG Design
JP Arockiasamy, LE Benjamin… - Security and …, 2021 - Wiley Online Library
JP Arockiasamy, LE Benjamin, RU Vaidyanathan
Security and Communication Networks, 2021•Wiley Online LibraryThe design of cryptographically secure pseudorandom number generator (CSPRNG)
producing unpredictable pseudorandom sequences robustly and credibly has been a
nontrivial task. Almost all the chaos‐based CSPRNG design approaches invariably depend
only on statistical analysis. Such schemes designed to be secure are being proven to be
predictable and insecure day by day. This paper proposes a design and instantiation
approach to chaos‐based CSPRNG using proven generic constructions of modern …
producing unpredictable pseudorandom sequences robustly and credibly has been a
nontrivial task. Almost all the chaos‐based CSPRNG design approaches invariably depend
only on statistical analysis. Such schemes designed to be secure are being proven to be
predictable and insecure day by day. This paper proposes a design and instantiation
approach to chaos‐based CSPRNG using proven generic constructions of modern …
The design of cryptographically secure pseudorandom number generator (CSPRNG) producing unpredictable pseudorandom sequences robustly and credibly has been a nontrivial task. Almost all the chaos‐based CSPRNG design approaches invariably depend only on statistical analysis. Such schemes designed to be secure are being proven to be predictable and insecure day by day. This paper proposes a design and instantiation approach to chaos‐based CSPRNG using proven generic constructions of modern cryptography. The proposed design approach with proper instantiation of such generic constructions eventually results in providing best of both worlds that is the provable security guarantees of modern cryptography and passing of necessary statistical tests as that of chaos‐based schemes. Also, we introduce a new coupled map lattice based on logistic‐sine map for the construction of CSPRNG. The proposed pseudorandom number generator is proven using rigorous security analysis as that of modern cryptography and tested using the standard statistical testing suites. It is observed that the generated sequences pass all stringent statistical tests such as NIST, Dieharder, ENT, and TestU01 randomness test suites.
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