Chaotic polynomial sequences for high-entropy stream ciphers
D. Balajibalaji@avit.ac.inDepartment of Humanities and Sciences (Mathematics Division)Aarupadai Veedu Institute of TechnologyVinayaka Mission’s Research Foundation (Deemed to be University)Paiyanoor, Chennai, Tamil Nadu, 603104, IndiaView full profile → , *Tanya SinghCorresponding authordean.academics@niu.edu.inSchool of Engineering & TechnologyNoida International UniversityGreater Noida, Uttar Pradesh, 203201, IndiaView full profile → , Nikhil Mohan Shindenikhil.shinde@vupune.ac.inDepartment of Mechanical EngineeringVishwakarma UniversityPune, Maharashtra, 411048, IndiaView full profile → , Rajesh Kumar Tripathirajesh.tripathi@gla.ac.inDepartment of Computer Engineering & ApplicationsGLA UniversityMathura, Uttar Pradesh, 281406, IndiaView full profile → , V. Dhanalakshmidhanalakshmiv@maher.ac.inDepartment of Computer ScienceMeenakshi College of Arts and ScienceMeenakshi Academy of Higher Education & Research (Deemed to be University)Chennai, Tamil Nadu, 600078, IndiaView full profile → , Kathirisetty Nikhilanikhila@vardhaman.orgDepartment of Computer Science and EngineeringVardhaman College of EngineeringShamshabad, Hyderabad, Telangana, 501218, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2026
- Published Online:
- 31 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JDMSC-3003
- Pages:
- 3713–3725
Abstract
The chaotic sequences of polynomials have a promising but underutilized basis on the design of high-entropy stream ciphers, to mitigate constraints of predictability and low randomness in the design of conventional generators. The present paper suggests a hybrid chaotic-polynomial model that incorporates nonlinear iterative map with adaptive coefficient perturbation. The model is also tested with NIST statistical test suites as well as real-time encryption benchmark on IoT data. The outcomes show the enhancement of entropy up to 0.998, which is 21.4 % more than with LFSR-based ciphers, and a 34.7 % decrease in correlation. The proposed method has an 18.2% better key sensitivity, and increased resistance to differential attacks when compared to the existing chaotic systems. Furthermore, the performance of the encryption process in the embedded devices (Raspberry Pi and ESP32) showed that high speed encryption (up to 224.7 Mbps) is possible with the proposed framework with relatively small memory consumption, which confirms the applicability of the proposed framework to the low resource-based secure IoT communication environment. The solution guarantees a scalable and secure communication provisioning a strong paradigm in next-generation cryptographic stream ciphers.
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References
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