263 research outputs found
Research on digital image watermark encryption based on hyperchaos
The digital watermarking technique embeds meaningful information into one or more watermark images hidden in one image, in which it is known as a secret carrier. It is difficult for a hacker to extract or remove any hidden watermark from an image, and especially to crack so called digital watermark. The combination of digital watermarking technique and traditional image encryption technique is able to greatly improve anti-hacking capability, which suggests it is a good method for keeping the integrity of the original image. The research works contained in this thesis include: (1)A literature review the hyperchaotic watermarking technique is relatively more advantageous, and becomes the main subject in this programme. (2)The theoretical foundation of watermarking technologies, including the human visual system (HVS), the colour space transform, discrete wavelet transform (DWT), the main watermark embedding algorithms, and the mainstream methods for improving watermark robustness and for evaluating watermark embedding performance. (3) The devised hyperchaotic scrambling technique it has been applied to colour image watermark that helps to improve the image encryption and anti-cracking capabilities. The experiments in this research prove the robustness and some other advantages of the invented technique. This thesis focuses on combining the chaotic scrambling and wavelet watermark embedding to achieve a hyperchaotic digital watermark to encrypt digital products, with the human visual system (HVS) and other factors taken into account. This research is of significant importance and has industrial application value
Entropy in Image Analysis III
Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future
Dynamic block encryption with self-authenticating key exchange
One of the greatest challenges facing cryptographers is the mechanism used
for key exchange. When secret data is transmitted, the chances are that there
may be an attacker who will try to intercept and decrypt the message. Having
done so, he/she might just gain advantage over the information obtained, or
attempt to tamper with the message, and thus, misguiding the recipient.
Both cases are equally fatal and may cause great harm as a consequence.
In cryptography, there are two commonly used methods of exchanging secret
keys between parties. In the first method, symmetric cryptography, the key is
sent in advance, over some secure channel, which only the intended recipient
can read. The second method of key sharing is by using a public key exchange
method, where each party has a private and public key, a public key is shared
and a private key is kept locally. In both cases, keys are exchanged between
two parties.
In this thesis, we propose a method whereby the risk of exchanging keys
is minimised. The key is embedded in the encrypted text using a process
that we call `chirp coding', and recovered by the recipient using a process
that is based on correlation. The `chirp coding parameters' are exchanged
between users by employing a USB flash memory retained by each user. If the
keys are compromised they are still not usable because an attacker can only
have access to part of the key. Alternatively, the software can be configured
to operate in a one time parameter mode, in this mode, the parameters
are agreed upon in advance. There is no parameter exchange during file
transmission, except, of course, the key embedded in ciphertext.
The thesis also introduces a method of encryption which utilises dynamic blocks, where the block size is different for each block. Prime numbers are
used to drive two random number generators: a Linear Congruential Generator
(LCG) which takes in the seed and initialises the system and a Blum-Blum
Shum (BBS) generator which is used to generate random streams to encrypt
messages, images or video clips for example. In each case, the key created is
text dependent and therefore will change as each message is sent.
The scheme presented in this research is composed of five basic modules. The
first module is the key generation module, where the key to be generated is
message dependent. The second module, encryption module, performs data
encryption. The third module, key exchange module, embeds the key into
the encrypted text. Once this is done, the message is transmitted and the
recipient uses the key extraction module to retrieve the key and finally the
decryption module is executed to decrypt the message and authenticate it.
In addition, the message may be compressed before encryption and decompressed
by the recipient after decryption using standard compression tools
The dynamics of complex systems. Studies and applications in computer science and biology
Our research has focused on the study of complex dynamics and on their use in both information security and bioinformatics. Our first work has been on chaotic discrete dynamical systems, and links have been established between these dynamics on the one hand, and either random or complex behaviors. Applications on information security are on the pseudorandom numbers generation, hash functions, informationhiding, and on security aspects on wireless sensor networks. On the bioinformatics level, we have applied our studies of complex systems to theevolution of genomes and to protein folding
Learning discrete word embeddings to achieve better interpretability and processing efficiency
L’omniprésente utilisation des plongements de mot dans le traitement des langues naturellesest la preuve de leur utilité et de leur capacité d’adaptation a une multitude de tâches. Ce-pendant, leur nature continue est une importante limite en terme de calculs, de stockage enmémoire et d’interprétation. Dans ce travail de recherche, nous proposons une méthode pourapprendre directement des plongements de mot discrets. Notre modèle est une adaptationd’une nouvelle méthode de recherche pour base de données avec des techniques dernier crien traitement des langues naturelles comme les Transformers et les LSTM. En plus d’obtenirdes plongements nécessitant une fraction des ressources informatiques nécéssaire à leur sto-ckage et leur traitement, nos expérimentations suggèrent fortement que nos représentationsapprennent des unités de bases pour le sens dans l’espace latent qui sont analogues à desmorphèmes. Nous appelons ces unités dessememes, qui, de l’anglaissemantic morphemes,veut dire morphèmes sémantiques. Nous montrons que notre modèle a un grand potentielde généralisation et qu’il produit des représentations latentes montrant de fortes relationssémantiques et conceptuelles entre les mots apparentés.The ubiquitous use of word embeddings in Natural Language Processing is proof of theirusefulness and adaptivity to a multitude of tasks. However, their continuous nature is pro-hibitive in terms of computation, storage and interpretation. In this work, we propose amethod of learning discrete word embeddings directly. The model is an adaptation of anovel database searching method using state of the art natural language processing tech-niques like Transformers and LSTM. On top of obtaining embeddings requiring a fractionof the resources to store and process, our experiments strongly suggest that our representa-tions learn basic units of meaning in latent space akin to lexical morphemes. We call theseunitssememes, i.e., semantic morphemes. We demonstrate that our model has a greatgeneralization potential and outputs representation showing strong semantic and conceptualrelations between related words
Entropy in Image Analysis II
Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas
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