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<p>Protecting cloud-stored image data remains a major challenge due to increasing security threats, regulatory compliance requirements, and the need for efficient encryption that ensures confidentiality without compromising performance. Traditional encryption methods often struggle to balance strong security, computational efficiency, and resilience against attacks. To address these issues, we propose a novel hybrid encryption scheme that combines Elliptic Curve Cryptography (ECC), chaotic Attribute-Based Encryption (ABE), and spatiotemporal chaos. This integration leverages the lightweight nature of ECC for efficiency, the fine-grained access control of ABE for flexible data sharing, and chaotic systems for enhanced randomness and diffusion. Experimental evaluations on standard test images demonstrate that our method achieves high security and robustness, featuring near-ideal entropy (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\sim 7.999\)</EquationSource> </InlineEquation>), high SSIM scores (0.9875 –0.9931), low correlation, and strong resistance to differential attacks (NPCR = 99.6094%, UACI = 33.4635%). These results confirm that the proposed approach outperforms existing methods in both security and computational efficiency, making it suitable for secure cloud-based image storage and transmission.</p>

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Enhancing image security based on cloud computing through hybrid encryption: combining ECC, ABE, and spatiotemporal cryptography

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Ismehene Chaouch,
  • Anis Naanaa,
  • Sadok El Asmi

摘要

Protecting cloud-stored image data remains a major challenge due to increasing security threats, regulatory compliance requirements, and the need for efficient encryption that ensures confidentiality without compromising performance. Traditional encryption methods often struggle to balance strong security, computational efficiency, and resilience against attacks. To address these issues, we propose a novel hybrid encryption scheme that combines Elliptic Curve Cryptography (ECC), chaotic Attribute-Based Encryption (ABE), and spatiotemporal chaos. This integration leverages the lightweight nature of ECC for efficiency, the fine-grained access control of ABE for flexible data sharing, and chaotic systems for enhanced randomness and diffusion. Experimental evaluations on standard test images demonstrate that our method achieves high security and robustness, featuring near-ideal entropy ( \(\sim 7.999\) ), high SSIM scores (0.9875 –0.9931), low correlation, and strong resistance to differential attacks (NPCR = 99.6094%, UACI = 33.4635%). These results confirm that the proposed approach outperforms existing methods in both security and computational efficiency, making it suitable for secure cloud-based image storage and transmission.