Novel structures of chaos-based parallel multiple image encryption and FPGA implementation
Notice bibliographique
Résumé
Image data has been generated massively by devices in medical imaging modalities, cameras, and even by artificial intelligence. Encryption is the powerful method to keep the image content confidential, in which an encryption algorithm must include the confusion and diffusion properties. For massive images, a efficient method of encryption must be chosen to meet the demands of encryption speed and confidentiality. So far, chaos-based image encryption has been an active topic of research because it is considered an effective method to remove the correlation in image data as well as to keep confidential by the involvement of chaotic system in the encryption process. Besides, multiple image encryption algorithms encrypt multiple images in parallel, and it provides highly efficient performance in term of speed if it is implemented on a parallel computing platform such as multiple core processing as well as digital hardware design. Chaos-based multiple image encryption is constructed by integrating a chaotic system into multiple image encryption. Recently, many algorithms of chaos-based multiple image encryption have been proposed, and they are proved to have high efficient in terms of both speed and confidentiality. However, all the existing algorithms of chaos-based multiple image encryption require images of the same size and of the same number of bits representing pixels. Further, they encrypt a cohort of plain images at the same time, and all ciphertext images of a cohort must also be decrypted at the same time. It means that if it does not allow to decrypt one or some selected ciphertext images from a cohort separately; and as a result, it wastes time and energy to decrypt unwanted images. In this paper, three novel structures of chaos-based multiple image encryption are proposed which overcome the drawbacks of existing algorithms. That is, the proposed cryptosystems accept cohort images of different sizes; pixels of images can be represented by different numbers of bits; and any selected ciphertext images from a cohort can be decrypted separately. The security is improved by using the session keys of image-content dependency. The proposed structures of multiple image encryption consist of permutation, substitution, and diffusion processes. The difference between three structures is the order of such processes. A perturbed chaotic map and a linear-feedback shift register are employed to generate pseudo-random bit sequences for session keys. The simulation results for the exemplar designs using the proposed structures show the effectiveness by means of the statistical analysis for the session keys using the NIST randomness test, information entropy, histogram, and correlation coefficients of adjacent pixels in ciphertext images, and security analysis by means of space and sensitivity of the secret key. The hardware implementation on the FPGA platform demonstrates the feasibility of the proposed structures by means of throughput and hardware efficiency.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».