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Advances in Decision Sciences (ADS)

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A New Approach for Image Security Enhancement Using Ternary Logic Linear Feedback Shift Register for Cryptographic Applications

A New Approach for Image Security Enhancement Using Ternary Logic Linear Feedback Shift Register for Cryptographic Applications

Title

A New Approach for Image Security Enhancement Using Ternary Logic Linear Feedback Shift Register for Cryptographic Applications

Authors

  • Trapti Sharma
    VIT Bhopal University, Bhopal-Indore Highway, Kotri Kalan, Sehore, 466114, Madhya Pradesh, India
  • Ayush Ranjan
    VIT Bhopal University, Bhopal-Indore Highway, Kotri Kalan, Sehore, 466114, Madhya Pradesh, India
  • Harvinder Singh
    VIT Bhopal University, Bhopal-Indore Highway, Kotri Kalan, Sehore, 466114, Madhya Pradesh, India
  • Rajit Nair
    VIT Bhopal University, Bhopal-Indore Highway, Kotri Kalan, Sehore, 466114, Madhya Pradesh, India
  • Hasan Alkahtani
    College of Computer Science and Information Technology, King Faisal University, P.O. Box 400, Al-Ahsa, 31982, Saudi Arabia
  • Sami Morsi
    Applied College, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
  • Ahmed A.F. Osman
    Applied College, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
  • Theyazn H.H. Aldhyani
    Applied College, King Faisal University, Al-Ahsa, 31982, Saudi Arabia

Abstract

Purpose: This paper addresses a core decision problem in healthcare data governance: how should healthcare decision-makers optimally select encryption parameters under resource and threat-model constraints? To answer this, a formal multi-criteria decision framework is developed and instantiated through a novel ternary linear feedback shift register (LFSR)-based encryption system, providing clinicians and security engineers with principled, quantitative parameter-selection guidance for lightweight image-encryption deployment on resource-constrained medical devices.
Design/Methodology/Approach: The proposed method extends traditional binary LFSRs to the ternary domain GF(3), operating over three logic states {0, 1, 2}, to generate pseudo-random keystreams that drive a pixel-permutation cypher. The system was evaluated on 10–15 images per modality across three clinically distinct modalities: kidney ultrasound, brain MRI, and multiple sclerosis (MS) MRI; reported metrics correspond to the image whose scores were closest to the modality average, ensuring representative rather than cherry-picked results. Evaluation used standard security metrics including NPCR, UACI, information entropy, MSE, PSNR, SSIM, and pixel-correlation coefficients.
Findings: The model achieves a Number of Pixels Change Rate (NPCR) of 98.04% and entropy of 6.80 bits for kidney ultrasound images and a Unified Average Changing Intensity (UACI) of 27.96% for brain MRI images. Encrypted images exhibit nearuniform histograms and near-zero pixel correlation coefficients (≤ 0.022), confirming strong randomness. Correct-key decryption recovers the original image with SSIM values of 0.9903–1.0000 and PSNR values of 44.52–52.21 dB. Incorrect-key decryption produces entirely unintelligible output, validating key sensitivity. The entropy gap below the 8-bit theoretical maximum is attributed to the permutation-only design, which preserves pixel intensity values; this limitation and the path towards a diffusion layer are discussed.
Originality/Value: This work makes two original contributions. The primary contribution is a formally grounded, evidence-based decision framework that maps LFSR configuration variables (n, P) to measurable security-versus-cost trade-offs across three healthcare deployment tiers, enabling risk-based governance of medical image encryption. The secondary contribution is the ternary LFSR cipher itself — the first deployment of GF(3) logic within an LFSR-based cypher for medical image protection — which serves as the concrete case study instantiating the decision framework, expanding the key space from 2n − 1 to 3n − 1 states while maintaining O(N logN) computational complexity.
Implications: The decision framework gives healthcare administrators and security engineers a structured, evidence-based basis for encryption parameter selection, directly supporting risk-based governance and regulatory compliance (e.g., HIPAA, GDPR). The minimax-regret analysis provides robust configuration guidance even under uncertainty about attacker capability and device heterogeneity. The low computational overhead of the ternary LFSR cipher makes the framework practically deployable on embedded and IoTbased medical devices. This work advances decision science methodology by formalizing parameter-selection under resource constraints and threat-model uncertainty—a canonical multi-criteria decision problem—and demonstrating its application to healthcare data governance, where encryption configuration choices directly impact regulatory compliance, patient privacy protection, and operational efficiency under bounded computational budgets.

Keywords

Ternary logic, linear feedback shift register, image encryption, cryptography, decision framework, parameter selection, risk-based governance, healthcare decisionmaking

Classification-JEL

C44, C61, I18, C88

Pages

184-214

How to Cite

Sharma, T., Ranjan, A., Singh, H., Nair, R., Alkahtani, H., Morsi, S., Osman, A. A. F., & Aldhyani, T. H. H. (2026). A New Approach for Image Security Enhancement Using Ternary Logic Linear Feedback Shift Register for Cryptographic Applications. Advances in Decision Sciences, 30(3), 184-214.

https://doi.org/10.47654/v30y2026i3p184-214

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ISSN 2090-3359 (Print)
ISSN 2090-3367 (Online)

Scientific and Business World

Asia University, Taiwan

8.3
2024CiteScore
 
88th percentile
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SCImago Journal & Country Rank
Q1 in Scopus
CiteScore 2024 = 8.3
CiteScoreTracker 2025 = 6.9
SNIP 2024 = 0.632
SJR Quartile = Q3
SJR 2025 = 0.240
H-Index = 18

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