# Chaotic Image Encryption: State-of-the-Art, Ecosystem, and Future Roadmap
## 6 Conclusions  
This paper presented of a comprehensive survey of existing work on chaotic image encryption and established an ecosystem, as well as a future roadmap for the field. We identified the challenges of the chaos aspect, the image aspect, and the encryption aspect of this research area. The choices among different chaos domains, sources, and dimensions, as well as the choice between block and stream ciphers or symmetric and asymmetric cryptography are some of these challenges. The work of this survey will help build a strong foundation from which further research can be built. While current research trends indicate a focus on AI and neural networks (chaotic neural networks, chaotic neural image encryption, etc. ), predicted trends lean towards quantum and bio-inspired AI (bio-inspired and quantum-inspired neural chaotic encryption). Further research can be performed to expand the ecosystem of chaotic image encryption as these new trends produce more novel results. [PERSON] has contributed to the review. [PERSON] has contributed in review, writing and preparation. All authors have read and agreed to the published version of the manuscript. This research received no external funding. * (17) [PERSON]; [PERSON]; [PERSON] A survey of image encryption algorithms. In Proceedings of the International Conference on Information Technology (ICIT), Amman, Jordan, 14-15 July 2021. * (18) [PERSON]; [PERSON] Image encryption techniques: A review. In Proceedings of the 10 th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 29-31 January 2020. * (19) [PERSON]; [PERSON] New direction of cryptography: A review on text-to-image encryption algorithms based on rgb color value. In Proceedings of the Seventh International Conference on Software Defined Systems (SDS), Paris, France, 20-23 April 2020. * (20) [PERSON]; [PERSON] A survey on the techniques of medical image encryption. In Proceedings of the IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Madurai, India, 13-15 December 2018. * (21) [PERSON]; [PERSON] Image encryption using chaotic maps: A survey. In Proceedings of the Fifth International Conference on Signal and Image Processing, Bangalore, India, 8-10 January 2014. * (22) [PERSON]; [PERSON] A state-of-art model of encrypting medical image using dna cryptography and hybrid chaos map--2d zaslavaski map: Review. In Proceedings of the 6 th International Conference on Devices, Circuits and Systems (ICDCS), Coimbatore, India, 21-22 April 2022. * (23) [PERSON]; [PERSON] Review of joint encoding and encryption for image transmission using chaotic map, Idpc and aes encryption. In Proceedings of the 6 th International Conference on Signal Processing, Computing and Control (ISPCC), Solan, India, 7-9 October 2021. * (24) [PERSON]; [PERSON]; [PERSON] A review of chaos based image encryption. In Proceedings of the 3 rd International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 27-29 March 2019. * (25) [PERSON] Overview of image encryption based on chaotic system. In Proceedings of the 2 nd International Conference on Computing and Data Science (CDS), Stanford, CA, USA, 28-29 January 2021. * (26) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Image encryption using chaotic techniques: A survey study. In Proceedings of the International Conference in Advances in Power, Signal, and Information Technology (APSIT), Bhubaneswar, India, 8-10 October 2021. * (27) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Comparative performance study on ordinary and chaos image encryption schemes. In Proceedings of the International Conference on Advanced Computing and Applications (ACOMP), Ho Chi Minh, Vietnam, 29 November-1 December 2017. * (28) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] On the synergies between machine learning and binocular stereo for depth estimation from images: A survey. _IEEE Trans. Pattern Anal. Mach. Intell._**2021**.