Parallel programming environment for OpenMP

We present our effort to provide a comprehensive parallel programming environment for the OpenMP parallel directive language. This environment includes a parallel programming methodology for the OpenMP programming model and a set of tools ( Ursa Minor and InterPol) that support this methodology. Our toolset provides automated and interactive assistance to parallel programmers in time-consuming tasks of the proposed methodology. The features provided by our tools include performance and program structure visualization, interactive optimization, support for performance modeling, and performance advising for finding and correcting performance problems. The presented evaluation demonstrates that our environment offers significant support in general parallel tuning efforts and that the toolset facilitates many common tasks in OpenMP parallel programming in an efficient manner

Privacy-preserving information hiding and its applications

The phenomenal advances in cloud computing technology have raised concerns about data privacy. Aided by the modern cryptographic techniques such as homomorphic encryption, it has become possible to carry out computations in the encrypted domain and process data without compromising information privacy. In this thesis, we study various classes of privacy-preserving information hiding schemes and their real-world applications for cyber security, cloud computing, Internet of things, etc. Data breach is recognised as one of the most dreadful cyber security threats in which private data is copied, transmitted, viewed, stolen or used by unauthorised parties. Although encryption can obfuscate private information against unauthorised viewing, it may not stop data from illegitimate exportation. Privacy-preserving Information hiding can serve as a potential solution to this issue in such a manner that a permission code is embedded into the encrypted data and can be detected when transmissions occur. Digital watermarking is a technique that has been used for a wide range of intriguing applications such as data authentication and ownership identification. However, some of the algorithms are proprietary intellectual properties and thus the availability to the general public is rather limited. A possible solution is to outsource the task of watermarking to an authorised cloud service provider, that has legitimate right to execute the algorithms as well as high computational capacity. Privacypreserving Information hiding is well suited to this scenario since it is operated in the encrypted domain and hence prevents private data from being collected by the cloud. Internet of things is a promising technology to healthcare industry. A common framework consists of wearable equipments for monitoring the health status of an individual, a local gateway device for aggregating the data, and a cloud server for storing and analysing the data. However, there are risks that an adversary may attempt to eavesdrop the wireless communication, attack the gateway device or even access to the cloud server. Hence, it is desirable to produce and encrypt the data simultaneously and incorporate secret sharing schemes to realise access control. Privacy-preserving secret sharing is a novel research for fulfilling this function. In summary, this thesis presents novel schemes and algorithms, including: • two privacy-preserving reversible information hiding schemes based upon symmetric cryptography using arithmetic of quadratic residues and lexicographic permutations, respectively. • two privacy-preserving reversible information hiding schemes based upon asymmetric cryptography using multiplicative and additive privacy homomorphisms, respectively. • four predictive models for assisting the removal of distortions inflicted by information hiding based respectively upon projection theorem, image gradient, total variation denoising, and Bayesian inference. • three privacy-preserving secret sharing algorithms with different levels of generality

Index to 1985 NASA Tech Briefs, volume 10, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1985 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Model-Based Scenario Testing and Model Checking with Applications in the Railway Domain

This thesis introduces Timed Moore Automata, a specification formalism, which extends the classical Moore Automata by adding the concept of abstract timers without concrete delay time values, which can be started and reset, and which can change their state from running to elapsed. The formalism is used in real-world railway domain applications, and algorithms for the automated test data generation and explicit model checking of Timed Moore Automata models are presented. In addition, this thesis deals with test data generation for larger scale test models using standardized modeling formalisms. An existing framework for the automated test data generation is presented, and its underlying work-flow is extended and modified in order to allow user interaction and guidance within the generation process. As opposed to specifying generation constraints for entire test scenarios, the modified work flow then allows for an iterative approach to elaborating and formalizing test generation goals

Software for malicious macro detection

The objective of this work is to give a detailed study of the development process of a software tool for the detection of the Emotet virus in Microsoft Office files, Emotet is a virus that has been wreaking havoc mainly in the business environment, from its beginnings as a banking Trojan to nowadays. In fact, this polymorphic family has managed to generate evident, incalculable and global inconveniences in the business activity without discriminating by corporate typology, affecting any company regardless of its size or sector, even entering into government agencies, as well as the citizens themselves as a whole. The existence of two main obstacles for the detection of this virus, constitute an intrinsic reality to it, on the one hand, the obfuscation in its macros and on the other, its polymorphism, are essential pieces of the analysis, focusing our tool in facing precisely two obstacles, descending to the analysis of the macros features and the creation of a neuron network that uses machine learning to recognize the detection patterns and deliberate its malicious nature. With Emotet's in-depth nature analysis, our goal is to draw out a set of features from the malicious macros and build a machine learning model for their detection. After the feasibility study of this project, its design and implementation, the results that emerge endorse the intention to detect Emotet starting only from the static analysis and with the application of machine learning techniques. The detection ratios shown by the tests performed on the final model, present a accuracy of 84% and only 3% of false positives during this detection process.Grado en Ingeniería Informátic

Fashion Industry

Fashion is a lot more than providing an answer to primary needs. It is a way of communication, of distinction, of proclaiming a unique taste and expressing the belonging to a group. Sometimes to an exclusive group. Currently, the fashion industry is moving towards hyperspace, to a multidimensional world that is springing from the integration of smart textiles and wearable technologies. It is far beyond aesthetics. New properties of smart textiles let designers experiment with astonishing forms and expressions. There are also surprising contrasts and challenges: a new life for natural fibers, sustainable fabrics and dyeing techniques, rediscovered by eco-fashion, and "artificial apparel," made of wearable electronic components. How is this revolution affecting the strategies of the fashion industry

Electronic Imaging & the Visual Arts. EVA 2019 Florence

The Publication is following the yearly Editions of EVA FLORENCE. The State of Art is presented regarding the Application of Technologies (in particular of digital type) to Cultural Heritage. The more recent results of the Researches in the considered Area are presented. Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; New Science and Culture Developments & Applications; New Technical Developments & Applications; Cultural Activities – Real and Virtual Galleries and Related Initiatives, Access to the Culture Information. One Workshop regards Innovation and Enterprise. The more recent results of the Researches at national and international level are reported in the Area of Technologies and Culture Heritage, also with experimental demonstrations of developed Activities

Depth Image-Based Rendering for Full Parallax Displays: Rendering, Compression, and Interpolation of Content for Autostereoscopic Poster and Video Displays

Advancements in production and display techniques allowed for novel displays to emerge that project a high-resolution light field for static poster content and video content, as well. These displays allow a full parallax, hence an audience can perceive a stereoscopic view of a scene without special glasses, which adjusts to the observer's position. The application of such displays are public places where the audience does not wear special glasses and is not restricted in movement. The rendering, storage, and transfer of the large amount of data required by those displays is a challenge. The image data for a static poster display is about 200 GB and the data rate for video displays are to be expected two to four orders of magnitude higher than HDTV. In this work the challenges are met by utilising DIBR to reduce the amount of data at the very beginning, during rendering. A fraction of the full amount of colour and depth images are rendered and used to interpolate the full data set. The rendering with state of the art ray tracers is described and a novel method to render image data for full parallax displays using OpenGL is contributed, that addresses some shortcomings of previous approaches. For static poster displays a scene based representation for image interpolation is introduced, which efficiently utilises multi-core processors and graphics hardware for parallelization, found on modern workstations. The introduced approach implements lossy compression of the input data, and handles arbitrary scenes, using a novel BNV selection algorithm. For video displays the real-time constraint does not allow for a costly interpolation or scene analysis. Hence, a novel approach is presented that uses a basic and computational inexpensive interpolation, and combines the interpolation results of different image representations without introducing prominent artefacts