{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T15:39:30Z","timestamp":1772465970170,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cryptography"],"abstract":"<jats:p>This article presents a novel framework for encrypting color images to enhance digital data security using deep learning and artificial intelligence techniques. The system employs a two-model neural architecture: the first, a Convolutional Neural Network (CNN), verifies sender authenticity during user authentication, while the second extracts unique fingerprint features. These features are converted into high-entropy encryption keys using Particle Swarm Optimization (PSO), minimizing key similarity and ensuring that no key is reused or transmitted. Keys are generated in real time simultaneously at both the sender and receiver ends, preventing interception or leakage and providing maximum confidentiality. Encrypted images are secured using the Advanced Encryption Standard (AES-256) with keys uniquely bound to each user\u2019s biometric identity, ensuring personalized privacy. Evaluation using security and encryption metrics yielded strong results: entropy of 7.9991, correlation coefficient below 0.00001, NPCR of 99.66%, UACI of 33.9069%, and key space of 2256. Although the final encryption employs an AES-256 key (key space of 2256), this key is derived from a much larger deep-key space of 28192 generated by multi-layer neural feature extraction and optimized via PSO, thereby significantly enhancing the overall cryptographic strength. The system also demonstrated robustness against common attacks, including noise and cropping, while maintaining recoverable original content. Furthermore, the neural models achieved classification accuracy exceeding 99.83% with an error rate below 0.05%, confirming the framework\u2019s reliability and practical applicability. This approach provides a secure, dynamic, and efficient image encryption paradigm, combining biometric authentication and AI-based feature extraction for advanced cybersecurity applications.<\/jats:p>","DOI":"10.3390\/cryptography10020016","type":"journal-article","created":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T14:06:56Z","timestamp":1772460416000},"page":"16","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Robust Image Encryption Framework Using Deep Feature Extraction and AES Key Optimization"],"prefix":"10.3390","volume":"10","author":[{"given":"Sahara A. S.","family":"Almola","sequence":"first","affiliation":[{"name":"Department of Computer Information Systems, College of Computer Science and Information Technology, University of Basrah, Basrah 61004, Iraq"}]},{"given":"Hameed A.","family":"Younis","sequence":"additional","affiliation":[{"name":"Department of Cyber Security, College of Computer Science and Information Technology, University of Basrah, Basrah 61004, Iraq"}]},{"given":"Raidah S.","family":"Khudeyer","sequence":"additional","affiliation":[{"name":"Department of Computer Information Systems, College of Computer Science and Information Technology, University of Basrah, Basrah 61004, Iraq"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"106480","DOI":"10.1016\/j.autcon.2025.106480","article-title":"Ensuring information security resilience in Digital-enabled Construction Projects (DCP) through quantum security technologies","volume":"179","author":"Blay","year":"2025","journal-title":"Autom. Constr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"100978","DOI":"10.1016\/j.measen.2023.100978","article-title":"Digital media system design and visual art analysis based on information security","volume":"31","author":"Li","year":"2024","journal-title":"Meas. Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1007\/s42979-024-03490-0","article-title":"Enhancing Secure Data Transmission Through Deep Learning-Based Image Steganography and Super-Resolution Generative Adversarial Networks","volume":"5","author":"Ramesh","year":"2024","journal-title":"SN Comput. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1007\/s10586-025-05295-z","article-title":"Advanced image encryption algorithm for Web3.0","volume":"28","author":"Zhou","year":"2025","journal-title":"Clust. Comput."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1007\/s42979-024-03382-3","article-title":"Evaluating ASCON Lightweight Encryption Algorithm for Image Encryption","volume":"5","author":"Alghamdi","year":"2024","journal-title":"SN Comput. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"108100","DOI":"10.1016\/j.rinp.2024.108100","article-title":"Dynamically scattering medium-based security-enhanced optical image encryption using orbital angular momentum and deep learning","volume":"69","author":"Hu","year":"2025","journal-title":"Results Phys."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"28553","DOI":"10.1007\/s00521-025-11558-y","article-title":"Logistics supply chain security risk warning system based on CNN-PSO encryption algorithm","volume":"37","author":"Feng","year":"2025","journal-title":"Neural Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1016\/j.procs.2025.04.076","article-title":"Integrating Blockchain and Quantum Key Exchange with Deep Learning for Enhanced Medical Data","volume":"259","author":"Sardar","year":"2025","journal-title":"Procedia Comput. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"101589","DOI":"10.1016\/j.rineng.2023.101589","article-title":"Internet of things for smart manufacturing based on advanced encryption standard (AES) algorithm with chaotic system","volume":"20","author":"Huo","year":"2023","journal-title":"Results Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1007\/s10586-025-05099-1","article-title":"An image encryption algorithm using a XOR enhanced 2D-Henon map","volume":"28","author":"Sharma","year":"2025","journal-title":"Clust. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Biryukov, A., and De Canni\u00e8re, C. (2025). Data Encryption Standard (DES). Encyclopedia of Cryptography, Security and Privacy, Springer Nature.","DOI":"10.1007\/978-3-030-71522-9_568"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"100759","DOI":"10.1016\/j.cosrev.2025.100759","article-title":"Advancements in image encryption: A comprehensive review of design principles and performance metrics","volume":"57","author":"Yogi","year":"2025","journal-title":"Comput. Sci. Rev."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1007\/s42519-024-00422-2","article-title":"Advances in Deep Learning for Medical Image Analysis: A Comprehensive Investigation","volume":"19","author":"Kumar","year":"2025","journal-title":"J. Stat. Theory Pract."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1007\/s10586-025-05341-w","article-title":"Enhancing multimodal biometric security through fundamental transforms and modified sigmoid fusion","volume":"28","author":"Badreddine","year":"2025","journal-title":"Clust. Comput."},{"key":"ref_15","first-page":"4851","article-title":"Hyper-Chaos and CNN-Based Image Encryption Scheme for Wireless Communication Transmission","volume":"84","author":"Liu","year":"2025","journal-title":"Comput. Mater. Contin."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"22667","DOI":"10.1007\/s00521-025-11083-y","article-title":"LEM-PSO: A lightweight evolutionary-state-driven multiple information learning particle swarm optimization algorithm","volume":"37","author":"Yang","year":"2025","journal-title":"Neural Comput. Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"16469","DOI":"10.1007\/s11356-025-36665-0","article-title":"Hybrid butterfly optimization and back propagation neural network for enhanced smart city data classification","volume":"32","author":"Natarajan","year":"2025","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"7369","DOI":"10.1007\/s13042-025-02660-7","article-title":"Crayfish optimization-based secure encryption of medical images with 7D hyperchaotic maps","volume":"16","author":"David","year":"2025","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"015206","DOI":"10.1088\/2631-8695\/ada3af","article-title":"An intelligent and efficient CNN-AES framework for image block encryption with a multi-key approach","volume":"7","author":"Saini","year":"2025","journal-title":"Eng. Res. Express"},{"key":"ref_20","first-page":"95","article-title":"Optimized AES with GAN Model for Secure Medical Image Transmission","volume":"13","author":"Vishnupriya","year":"2025","journal-title":"Int. J. Recent Innov. Trends Comput. Commun."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"126","DOI":"10.3390\/jcp4010007","article-title":"Image Encryption Algorithms: A Survey of Design and Evaluation Metrics","volume":"4","author":"Alghamdi","year":"2024","journal-title":"J. Cybersecur. Priv."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wang, J., Song, X., and El-Latif, A.A.A. (2022). Single-Objective Particle Swarm Optimization-Based Chaotic Image Encryption Scheme. Electronics, 11.","DOI":"10.3390\/electronics11162628"},{"key":"ref_23","unstructured":"Nair, B.V., Muni, S.S., and Durdu, A. (2024). Deep learning and chaos: A combined approach to image encryption and decryption. arXiv."},{"key":"ref_24","first-page":"114","article-title":"Convolutional Neural Network-Based Data Encryption Model for Multimedia Files Using Advanced Encryption Standard Algorithm","volume":"2","author":"Asaolu","year":"2025","journal-title":"UNIABUJA J. Eng. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"42379","DOI":"10.1007\/s11042-025-20840-z","article-title":"Lightweight secure image encryption: A tent map chaos theory approach","volume":"84","author":"Odeh","year":"2025","journal-title":"Multimed. Tools Appl."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Singh, M., Sood, S.K., and Bhatia, M. (2025). Post-quantum Cryptography: A Review on Cryptographic Solutions for the Era of Quantum Computing. Arch. Comput. Methods Eng., 1\u201342.","DOI":"10.1007\/s11831-025-10412-7"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4499","DOI":"10.1007\/s42107-025-01443-3","article-title":"Neural networks, CNNs, and hybrid models in structural retrofitting: A deep learning perspective","volume":"26","author":"Bhadauria","year":"2025","journal-title":"Asian J. Civ. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"301","DOI":"10.58496\/MJCS\/2025\/019","article-title":"Robust and Efficient Methods for Key Generation using Chaotic Maps and A2C Algorithm","volume":"5","author":"Mahdi","year":"2025","journal-title":"Mesopotamian J. Cybersecur."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"126612","DOI":"10.1016\/j.eswa.2025.126612","article-title":"Robust feature enhanced deep kernel support vector machine via low rank representation and clustering","volume":"271","author":"Li","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4133","DOI":"10.1007\/s13042-024-02139-x","article-title":"PSO-ECM: Particle swarm optimization-based evidential C-means algorithm","volume":"15","author":"Cai","year":"2024","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1007\/s10586-025-05543-2","article-title":"Dholes-inspired optimization (DIO): A nature-inspired algorithm for engineering optimization problems","volume":"28","author":"Mirjalili","year":"2025","journal-title":"Clust. Comput."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1186\/s43067-024-00168-8","article-title":"A novel improvement of particle swarm optimization using an improved velocity update function based on local best murmuration particle","volume":"11","author":"Twumasi","year":"2024","journal-title":"J. Electr. Syst. Inf. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"112617","DOI":"10.1016\/j.asoc.2024.112617","article-title":"Balancing convergence and diversity preservation in dual search space for large scale particle swarm optimization","volume":"169","author":"Guo","year":"2025","journal-title":"Appl. Soft Comput."},{"key":"ref_34","first-page":"101211","article-title":"Secured and effective task scheduling in cloud computing using Levy Flight\u2014Secretary Bird Optimization and Hash-based Message Authentication Code\u2014Secure Hash Authentication 256","volume":"48","author":"Gouse","year":"2025","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"129860","DOI":"10.1016\/j.eswa.2025.129860","article-title":"Adaptive energy management for battery swapping stations using HMDE-PSO: Optimizing charge-discharge control against cyber-physical attacks","volume":"298","author":"Jirdehi","year":"2026","journal-title":"Expert Syst. Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10044-024-01231-w","article-title":"Hierarchical contrastive learning and color standardization for single image sand-dust removal","volume":"27","author":"Si","year":"2024","journal-title":"Pattern Anal. Appl."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Singh, P., Dutta, S., and Pranav, P. (2024). Optimizing GANs for Cryptography: The Role and Impact of Activation Functions in Neural Layers Assessing the Cryptographic Strength. Appl. Sci., 14.","DOI":"10.3390\/app14062379"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Aslan, M., Do\u011fanaksoy, A., Sayg\u0131, Z., S\u00f6nmez Turan, M., and Sulak, F. (2025). Observations on NIST SP 800-90B entropy estimators. Cryptogr. Commun.","DOI":"10.1007\/s12095-025-00778-7"},{"key":"ref_39","first-page":"22","article-title":"Enhancing image encryption using histogram analysis, adjacent pixel autocorrelation test in chaos-based framework","volume":"186","author":"Taylor","year":"2024","journal-title":"Int. J. Comput. Appl."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"53","DOI":"10.32604\/iasc.2024.059691","article-title":"Innovative Lightweight Encryption Schemes Leveraging Chaotic Systems for Secure Data Transmission","volume":"40","author":"Alsaad","year":"2025","journal-title":"Intell. Autom. Soft Comput."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Foreman, C., Yeung, R., and Curchod, F.J. (2024). Statistical Testing of Random Number Generators and Their Improvement Using Randomness Extraction. Entropy, 26.","DOI":"10.3390\/e26121053"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1007\/s40747-025-01842-8","article-title":"A lightweight vision transformer with weighted global average pooling: Implications for IoMT applications","volume":"11","author":"Dong","year":"2025","journal-title":"Complex Intell. Syst."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"906","DOI":"10.5377\/nexo.v36i06.17447","article-title":"Key generation method from fingerprint image based on deep convolutional neural network model","volume":"36","author":"Hashem","year":"2023","journal-title":"Nexo Rev. Cient\u00edfica"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Saeed, F., Hussain, M., and Aboalsamh, H.A. (2022). Automatic Fingerprint Classification Using Deep Learning Technology (Deep-FKTNet). Mathematics, 10.","DOI":"10.3390\/math10081285"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"4329","DOI":"10.1002\/int.22782","article-title":"Fingerprint bio-key generation based on a deep neural network","volume":"37","author":"Wu","year":"2022","journal-title":"Int. J. Intell. Syst."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"14148","DOI":"10.48084\/etasr.7181","article-title":"Enhancing Data Security through Machine Learning-based Key Generation and Encryption","volume":"14","author":"Saini","year":"2024","journal-title":"Eng. Technol. Appl. Sci. Res."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Nguyen, H.T., and Nguyen, L.T. (2019). Fingerprints Classification through Image Analysis and Machine Learning Method. Algorithms, 12.","DOI":"10.3390\/a12110241"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Saeed, F., Hussain, M., and Aboalsamh, H.A. (2018, January 25\u201326). Classification of live scanned fingerprints using histogram of gradient descriptor. Proceedings of the 2018 21st Saudi Computer Society National Computer Conference (NCC), Riyadh, Saudi Arabia.","DOI":"10.1109\/NCG.2018.8592949"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Saeed, F., Hussain, M., and Aboalsamh, H.A. (2018, January 4\u20136). Classification of Live Scanned Fingerprints using Dense SIFT based Ridge Orientation Features. Proceedings of the 2018 1st International Conference on Computer Applications & Information Security (ICCAIS), Riyadh, Saudi Arabia.","DOI":"10.1109\/CAIS.2018.8442042"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"29439","DOI":"10.1038\/s41598-025-14784-5","article-title":"A high-entropy image encryption scheme using optimized chaotic maps with Josephus permutation strategy","volume":"15","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"105151","DOI":"10.1109\/ACCESS.2025.3575935","article-title":"Security-Enhanced Image Encryption: Combination of S-Boxes and Hyperchaotic Integrated Systems","volume":"13","author":"Song","year":"2025","journal-title":"IEEE Access"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Alexan, W., ElBeltagy, M., and Aboshousha, A. (2022). RGB Image Encryption through Cellular Automata, S-Box and the Lorenz System. Symmetry, 14.","DOI":"10.3390\/sym14030443"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Rakhra, M., Singh, P., Singhal, A., Singh, P., Sarkar, T., and Kumar, A. (2025, January 4\u20136). Optimizing Energy Efficiency in Public Sector Cloud Data Centers Through Machine Learning Driven Steganographic Manner. Proceedings of the 2025 3rd International Conference on Communication, Security, and Artificial Intelligence (ICCSAI), Greater Noida, India.","DOI":"10.1109\/ICCSAI64074.2025.11064553"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"22164","DOI":"10.1038\/s41598-025-07211-2","article-title":"Comparative analysis of sandstone microtomographic image segmentation using advanced convolutional neural networks with pixelwise and physical accuracy evaluation","volume":"15","author":"Hayatdavoudi","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Guo, L., Zhang, J., Zhu, T., Xiao, S., Liu, Y., and Li, B. (2024). Study on the Influence of Collision Scene on the Energy Dissipation Process for Train Collision. Appl. Sci., 15.","DOI":"10.3390\/app15010084"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Fan, W., Li, T., Wu, J., and Wu, J. (2023). Chaotic Color Image Encryption Based on Eight-Base DNA-Level Permutation and Diffusion. Entropy, 25.","DOI":"10.3390\/e25091268"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1465","DOI":"10.18280\/ijsse.140514","article-title":"Enhanced Image Encryption Using a Novel Chaotic System and Scramble Dithering Technique","volume":"14","author":"Jasim","year":"2024","journal-title":"Int. J. Saf. Secur. Eng."},{"key":"ref_58","first-page":"219","article-title":"Optimized Color Image Encryption Using Arnold Transform, URUK Chaotic Map and GWO Algorithm","volume":"7","author":"Abed","year":"2024","journal-title":"J. Port Sci. Res."},{"key":"ref_59","unstructured":"Belam, M. (2025). Deimos Cipher: A High-Entropy, Secure Encryption Algorithm with Strong Diffusion and Key Sensitivity. Cryptol. Eprint Arch."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"19499","DOI":"10.1038\/s41598-025-95511-y","article-title":"An image encryption scheme using 4-D chaotic system and cellular automaton","volume":"15","author":"Nadeem","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1049\/iet-ipr.2019.0771","article-title":"Novel multiple images encryption algorithm using CML system and DNA encoding","volume":"14","author":"Zhang","year":"2020","journal-title":"IET Image Process."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Moya-Albor, E., Romero-Arellano, A., Brieva, J., and Gomez-Coronel, S.L. (2023). Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton\u2019s Ant. Mathematics, 11.","DOI":"10.3390\/math11102396"}],"container-title":["Cryptography"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2410-387X\/10\/2\/16\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T14:47:01Z","timestamp":1772462821000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2410-387X\/10\/2\/16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,2]]},"references-count":62,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["cryptography10020016"],"URL":"https:\/\/doi.org\/10.3390\/cryptography10020016","relation":{},"ISSN":["2410-387X"],"issn-type":[{"value":"2410-387X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,2]]}}}