A survey of image encryption schemes: Arnold transformation, chaos, bit-plane extraction and permutation based algorithms

Abstract Securing digital images captured by unmanned aerial vehicles (UAVs) is important for maintaining data confidentiality and integrity during transmission over insecure networks. This study surveys and evaluates existing encryption schemes such as Arnold transformation, chaos-based, bit-plane extraction, quantum, and permutation-based algorithms. The existing image encryption algorithms are implemented and tested in MATLAB 2015 using standard benchmark images (Quantum, Baboon, and Cameraman), selected for their frequent use and benchmark relevance in recent image security literature. For algorithms whose statistical indices are already documented in prior research, those published values are adopted for reference. In cases where such data were unavailable, the corresponding schemes were re-implemented and experimentally evaluated in MATLAB 2015 to produce consistent and reproducible performance results. The comparative statistical analysis across these datasets demonstrates that hybrid quantum–chaotic and permutation–diffusion methods achieve near-ideal entropy values ( $$\approx $$ 7.999), high NPCR ( $$\approx $$ 99.6%), and UACI ( $$\approx $$ 33.4%). This indicates strong resistance to statistical and differential attacks. These schemes also exhibit low correlation coefficients (< 0.002) and large key spaces (> $$2^{100}$$ ).