Securing Language – Based Texts: Logistic Map Randomization in SIMON Encryption

Protecting language-oriented textual data has emerged as a paramount necessity in the contemporary global context. In a world where text acts as a primary communication medium through emails, messaging applications, social networking sites, and electronic documents, this text's security may lead to severe breaches of privacy, intellectual property theft, and leakage of confidential information. Text-based language encryption competent enough has recently protected access and ensured the integrity and confidentiality of data for varied communication needs. This paper develops a novel method for providing the secure encoding of language-based text information using a key-based logistic map of the SIMON encryption scheme. Traditional schemes for language-based text information encryption often suffer from performance or security deficits when implemented to manage a large corpus of information. By changing the SIMON cipher using keys from a chaotic logistic map, this algorithm attains considerable unpredictability and higher randomness, which are significant elements in efficient encryption. The chaotic nature inherent to the logistic map enhances the generation process of keys to ensure each instance of encryption utilizes unique, non-repetitive keys that cannot be forecasted or replicated. This method provides secure encryption for language-based text data, making it suitable for applications in secure messaging, protecting sensitive documents, and maintaining confidentiality in IoT-based language processing systems. Rigorous testing with the NIST SP 800-22 suite using a pass rate of 99.9% confirmed the enhanced randomness and resilience of the key generation schema against cryptographic attacks. However, the randomness of the ciphertexts is to be enhanced.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/iccsp64183.2025.11088773
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
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article

Securing Language – Based Texts: Logistic Map Randomization in SIMON Encryption

Ramapurath S. Jayasree, S Yaswanth, R. Sivaraman
Chaos-based Image/Signal Encryption
article

Securing Language – Based Texts: Logistic Map Randomization in SIMON Encryption

Ramapurath S. Jayasree, S Yaswanth, R. Sivaraman
article en

Abstract

Protecting language-oriented textual data has emerged as a paramount necessity in the contemporary global context. In a world where text acts as a primary communication medium through emails, messaging applications, social networking sites, and electronic documents, this text's security may lead to severe breaches of privacy, intellectual property theft, and leakage of confidential information. Text-based language encryption competent enough has recently protected access and ensured the integrity and confidentiality of data for varied communication needs. This paper develops a novel method for providing the secure encoding of language-based text information using a key-based logistic map of the SIMON encryption scheme. Traditional schemes for language-based text information encryption often suffer from performance or security deficits when implemented to manage a large corpus of information. By changing the SIMON cipher using keys from a chaotic logistic map, this algorithm attains considerable unpredictability and higher randomness, which are significant elements in efficient encryption. The chaotic nature inherent to the logistic map enhances the generation process of keys to ensure each instance of encryption utilizes unique, non-repetitive keys that cannot be forecasted or replicated. This method provides secure encryption for language-based text data, making it suitable for applications in secure messaging, protecting sensitive documents, and maintaining confidentiality in IoT-based language processing systems. Rigorous testing with the NIST SP 800-22 suite using a pass rate of 99.9% confirmed the enhanced randomness and resilience of the key generation schema against cryptographic attacks. However, the randomness of the ciphertexts is to be enhanced.

SASTRA University (IN)
Openalex Percentile: Top 81%
Chaos-based Image/Signal Encryption
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