Detta examensarbete reder ut arbetsprinciperna för olika typer av hårddiskskrivskydd; hårdvaruskrivskydd, mjukvaruskrivskydd, hybridskrivskydd och bygelskrivskydd. Slutsatsen av utredningen är att endast hårdvaruskrivskydd Detta examensarbete reder ut arbetsprinciperna för olika typer av hårddiskskrivskydd; hårdvaruskrivskydd, mjukvaruskrivskydd, hybridskrivskydd och bygelskrivskydd. Slutsatsen av utredningen är att endast hårdvaruskrivskydd bedöms ha tillräckligt pålitliga skyddsprinciper, vilket motiveras av dess oberoende från både hårdvara och operativsystem. Vidare undersöks hårdvaruskrivskyddet Image MASSter(TM) Drive Lock från Intelligent Computer Solutions (ICS). Några egentliga slutsatser gick inte dra av kretskonstruktionen, bortsett från att den är uppbyggd kring en FPGA (Xilinx Spartan-II, XC2S15) med tillhörande PROM (XC17S15APC). En egenutvecklad idé till autenticieringsmetod för hårddiskkloner föreslås som ett tillägg till arbetet. Principen bygger på att komplettera hårddiskklonen med unik information om hårddisk såväl kloningsomständigheter, vilka sammanflätas genom XOR-operation av komponenternas hashsummor.Autenticieringsmetoden kan vid sjösättning möjligen öka rättsäkerheten för både utredarna och den som står misstänkt vid en brottsutredning. Arbetet är till stora delar utfört vid och på uppdrag av Statens kriminaltekniska laboratorium (SKL) i Linköping.

Les caractéristiques locales sont essentielles dans de nombreux domaines de l’analyse d’images comme la détection et la reconnaissance d’objets, la recherche d’images, etc. Ces dernières années, plusieurs détecteurs dits locaux ont été proposés pour extraire de telles caractéristiques. Ces détecteurs locaux fonctionnent généralement bien pour certaines applications, mais pas pour toutes. Prenons, par exemple, une application de recherche dans une large base d’images. Dans ce cas, un détecteur à base de caractéristiques binaires pourrait être préféré à un autre exploitant des valeurs réelles. En effet, la précision des résultats de recherche pourrait être moins bonne tout en restant raisonnable, mais probablement avec un temps de réponse beaucoup plus court. En général, les détecteurs locaux sont utilisés en combinaison avec une méthode d’indexation. En effet, une méthode d’indexation devient nécessaire dans le cas où les ensembles de points traités sont composés de milliards de points, où chaque point est représenté par un vecteur de caractéristiques de grande dimension. / Local features are of central importance to deal with many different problems in image analysis and understanding including image registration, object detection and recognition, image retrieval, etc. Over the years, many local detectors have been presented to detect such features. Such a local detector usually works well for some particular applications but not all. Taking an application of image retrieval in large database as an example, an efficient method for detecting binary features should be preferred to other real-valued feature detection methods. The reason is easily seen: it is expected to have a reasonable precision of retrieval results but the time response must be as fast as possible. Generally, local features are used in combination with an indexing scheme. This is highly needed for the case where the dataset is composed of billions of data points, each of which is in a high-dimensional feature vector space.

The thesis is focused on the topic of virtual cryptocurrency Bitcoin. The theoretical part is divided into several chapters. First of all, there is a chapter containing basic information about the currency's history, its development to the present, as well as principles of operation of this currency. Because it is a currency based on cryptographic principles next chapter summarizing cryptographic techniques, which is necessary to know for subsequent analysis of this currency. In other parts is elaborated a detailed analysis of the principles of Bitcoin. The main point of this analysis is a system of transactions, decentralized history, then joining the transactions into blocks and in the end creating blockchain. It also explains the principle of P2P networks. The practical part of this work focuses on the analysis and design of payment applications for mobile devices. There used open-source libraries such BitcoinJ. The application is developed in Java programming language with plugin for portable devices, which work under the operating system Android. For the purposes of analysis and design of graphical user interface is used UML diagrams. The specification of the UML diagrams was utilized by freely available graphics software and the result is also included in this work.

My Master's thesis deals with the problems of flow compression in network devices. Its outcome should alleviate memory consumption of the flows and simplify the processing of network traffic. As an introduction I provide a description of protocols serving for data storage and manipulation, followed by discussion about possibilities of compression methods that are employed nowadays. In the following part there is an in-depth analysis of source data that shows the structure and composition of the data and brings up useful observations, which are later used in the testing  of existing compression methods, as well as about their potential and utilization in flow compression. Later on, I venture into the field of lossy compression and basing on the test results a new approach is described, created by means of flow clustering and their subsequent lossy compression. The conclusion contains an evaluation of the possibilities of the method and the final summary of the thesis along with various suggestions for further development of the research.

This document is trying to introduce the reader with issues of identifying the face connected with miscellaneous scanning technologies and enviroments. Inside this document there are mentioned some possibilities of creation unique print of a face so that there would be denied unwanted effects of enviroment and the identification of persons would be possible.

This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.

Cette thèse par article se compose de quatre articles qui contribuent au domaine de l’apprentissage profond, en particulier dans la compréhension et l’apprentissage des ap- proches neuronales des systèmes de dialogue. Le premier article fait un pas vers la compréhension si les architectures de dialogue neuronal couramment utilisées capturent efficacement les informations présentes dans l’historique des conversations. Grâce à une série d’expériences de perturbation sur des ensembles de données de dialogue populaires, nous constatons que les architectures de dialogue neuronal couramment utilisées comme les modèles seq2seq récurrents et basés sur des transformateurs sont rarement sensibles à la plupart des perturbations du contexte d’entrée telles que les énoncés manquants ou réorganisés, les mots mélangés, etc. Le deuxième article propose d’améliorer la qualité de génération de réponse dans les systèmes de dialogue de domaine ouvert en modélisant conjointement les énoncés avec les attributs de dialogue de chaque énoncé. Les attributs de dialogue d’un énoncé se réfèrent à des caractéristiques ou des aspects discrets associés à un énoncé comme les actes de dialogue, le sentiment, l’émotion, l’identité du locuteur, la personnalité du locuteur, etc. Le troisième article présente un moyen simple et économique de collecter des ensembles de données à grande échelle pour modéliser des systèmes de dialogue orientés tâche. Cette approche évite l’exigence d’un schéma d’annotation d’arguments complexes. La version initiale de l’ensemble de données comprend 13 215 dialogues basés sur des tâches comprenant six domaines et environ 8 000 entités nommées uniques, presque 8 fois plus que l’ensemble de données MultiWOZ populaire. / This thesis by article consists of four articles which contribute to the field of deep learning, specifically in understanding and learning neural approaches to dialog systems. The first article takes a step towards understanding if commonly used neural dialog architectures effectively capture the information present in the conversation history. Through a series of perturbation experiments on popular dialog datasets, wefindthatcommonly used neural dialog architectures like recurrent and transformer-based seq2seq models are rarely sensitive to most input context perturbations such as missing or reordering utterances, shuffling words, etc. The second article introduces a simple and cost-effective way to collect large scale datasets for modeling task-oriented dialog systems. This approach avoids the requirement of a com-plex argument annotation schema. The initial release of the dataset includes 13,215 task-based dialogs comprising six domains and around 8k unique named entities, almost 8 times more than the popular MultiWOZ dataset. The third article proposes to improve response generation quality in open domain dialog systems by jointly modeling the utterances with the dialog attributes of each utterance. Dialog attributes of an utterance refer to discrete features or aspects associated with an utterance like dialog-acts, sentiment, emotion, speaker identity, speaker personality, etc. The final article introduces an embedding-free method to compute word representations on-the-fly. This approach significantly reduces the memory footprint which facilitates de-ployment in on-device (memory constraints) devices. Apart from being independent of the vocabulary size, we find this approach to be inherently resilient to common misspellings.