A Self-Adaptive Bald Eagle Optimized Hybrid Chaotic Framework for Hyperspectral Image Encryption with Reversible Traceability and Merkle-Tree Integrity Verification

In this article, a hybrid security framework has been presented for hyperspectral images. This framework combines the three-stage chaotic core that is lightweight, along with the autonomous optimization of parameters through the use of SABES and the reversible traceability of ownership through PEL. The integrity of the images is verified by the Merkle Hash Tree, and this entire process is carried out through the parallel processing of data. The HSI cubes having 204 bands have been tested over this hybrid security framework, and the results are near-perfect in terms of entropy (7.95-7.99 bits), almost no correlation (0.01-0.03), as well as good resistance against differential attacks (the NPCR is approx 99.6% and UACI is about 33.4%). There is also a space of keys of about 2³²⁵. It can be concluded that this framework can be used to protect   huge   hyperspectral   data   in   applications   such   as   defense/security. Some examples of the future research include exploring how hardware acceleration using FPGA technologies can support the chaos core and the fitness analysis of the SABES algorithm in real-time encryption for live satellite or drone videos; studying how to keep Merkle tree roots and water mark extraction data decentralized using a block chain solution; extending the 3D scrambler-diffuser architecture to other 3D imaging methods such as MRI and CT scans offering the same benefits in medical applications.

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