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<p>This paper introduces Paper-Folding-Crypto (PFC), a novel hybrid encryption framework that combines AES-GCM with spatial transformation techniques inspired by geometric paper folding operations. The PFC architecture employs a three-tiered approach consisting of Dynamic Block Chaining using authenticated encryption for strategically selected anchor blocks, Static Paper Folding for systematic spatial diffusion, and Adaptive Corner Folding for key-dependent geometric diversity. Our framework addresses the fundamental tension between cryptographic strength and computational efficiency by leveraging hardware-accelerated AES for critical security operations while employing efficient XOR-based spatial transformations for comprehensive image protection. Experimental evaluation on medical images, including chest X-rays, brain MRI, and ultrasound, demonstrates significant performance improvements, with encryption times reducing from 208.8<i>ms</i> to 0.78<i>ms</i> for 64<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\times\)</EquationSource> </InlineEquation>64 block sizes compared to traditional approaches. Security analysis confirms resistance to differential attacks, strong statistical properties with uniform histogram distribution, and provable security reduction to AES-256-GCM. The proposed method achieves <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(O(\log N)\)</EquationSource> </InlineEquation> computational complexity while maintaining diagnostic image quality, making it particularly suitable for real-time medical IoT applications where both security and performance are critical requirements.</p>

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Paper-Folding-Crypto - A lightweight hybrid encryption framework for medical IoT image security

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Saleem Alsaraireh,
  • Yousef AbuHour,
  • Ashraf Ahmad

摘要

This paper introduces Paper-Folding-Crypto (PFC), a novel hybrid encryption framework that combines AES-GCM with spatial transformation techniques inspired by geometric paper folding operations. The PFC architecture employs a three-tiered approach consisting of Dynamic Block Chaining using authenticated encryption for strategically selected anchor blocks, Static Paper Folding for systematic spatial diffusion, and Adaptive Corner Folding for key-dependent geometric diversity. Our framework addresses the fundamental tension between cryptographic strength and computational efficiency by leveraging hardware-accelerated AES for critical security operations while employing efficient XOR-based spatial transformations for comprehensive image protection. Experimental evaluation on medical images, including chest X-rays, brain MRI, and ultrasound, demonstrates significant performance improvements, with encryption times reducing from 208.8ms to 0.78ms for 64 \(\times\) 64 block sizes compared to traditional approaches. Security analysis confirms resistance to differential attacks, strong statistical properties with uniform histogram distribution, and provable security reduction to AES-256-GCM. The proposed method achieves \(O(\log N)\) computational complexity while maintaining diagnostic image quality, making it particularly suitable for real-time medical IoT applications where both security and performance are critical requirements.