A Novel Lightweight Cryptographic Framework Based on Hybrid Chaotic Maps and <scp>DNA</scp> Encoding

ABSTRACT With the increasing reliance on IoT‐based healthcare systems, securing sensitive medical images against unauthorized access and cyber threats has become a critical challenge. Conventional encryption methods, such as the Advanced Encryption Standard (AES) and the Data Encryption Standard (DES), require significant computational resources, making them impractical for IoT devices with limited processing power. This paper presents a novel lightweight method for encrypting medical images with DNA cryptography. It generates robust and striking key control sequences with a Hybrid Logistic–Tent map. Bifurcation and Lyapunov exponent research demonstrate that this hybrid map resolves the challenges associated with conventional chaotic systems by eliminating periodic windows and enhancing unpredictability. Attackers find it difficult to penetrate due to the application of advanced chaotic behavior that regulates the selection of DNA rules and pixel permutations. The proposed map is integral to the encryption framework and is evaluated independently and contrasted with other established maps, such as Logistic, Tent, Henon, and Logistic‐Sine. The proposed method has exceptional security features, as indicated by a Shannon entropy of 7.80, high NPCR and UACI scores, and low correlation coefficients. Using less than ∼64 Kb of RAM for a 256 × 256 image makes this computationally efficient approach very suitable for real‐time medical IoT applications. Experimental results confirm that the proposed model, while preserving a lightweight and scalable architecture, outperforms many existing approaches regarding randomness, key sensitivity, and resistance to statistical attacks.

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Publication Details

Journal
Security and Privacy
Published
2025-09-01
DOI
https://doi.org/10.1002/spy2.70097
Citations
1
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
1.28
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article

A Novel Lightweight Cryptographic Framework Based on Hybrid Chaotic Maps and DNA Encoding

Mohammad Ubaidullah Bokhari, Basil Hanafi, Md. Zeyauddin, Sarfaraz Ahmad et al.
1 citations
Security and Privacy
Chaos-based Image/Signal Encryption
1.28
article

A Novel Lightweight Cryptographic Framework Based on Hybrid Chaotic Maps and DNA Encoding

Mohammad Ubaidullah Bokhari, Basil Hanafi, Md. Zeyauddin, Sarfaraz Ahmad, Shahnwaz Afzal
article en
1 citations

Abstract

ABSTRACT With the increasing reliance on IoT‐based healthcare systems, securing sensitive medical images against unauthorized access and cyber threats has become a critical challenge. Conventional encryption methods, such as the Advanced Encryption Standard (AES) and the Data Encryption Standard (DES), require significant computational resources, making them impractical for IoT devices with limited processing power. This paper presents a novel lightweight method for encrypting medical images with DNA cryptography. It generates robust and striking key control sequences with a Hybrid Logistic–Tent map. Bifurcation and Lyapunov exponent research demonstrate that this hybrid map resolves the challenges associated with conventional chaotic systems by eliminating periodic windows and enhancing unpredictability. Attackers find it difficult to penetrate due to the application of advanced chaotic behavior that regulates the selection of DNA rules and pixel permutations. The proposed map is integral to the encryption framework and is evaluated independently and contrasted with other established maps, such as Logistic, Tent, Henon, and Logistic‐Sine. The proposed method has exceptional security features, as indicated by a Shannon entropy of 7.80, high NPCR and UACI scores, and low correlation coefficients. Using less than ∼64 Kb of RAM for a 256 × 256 image makes this computationally efficient approach very suitable for real‐time medical IoT applications. Experimental results confirm that the proposed model, while preserving a lightweight and scalable architecture, outperforms many existing approaches regarding randomness, key sensitivity, and resistance to statistical attacks.

Security and PrivacyVol. 8(5)
Aligarh Muslim University (IN)
Openalex Percentile: Top 16%
Chaos-based Image/Signal Encryption
1.28
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