Multi­Factor and Continuous Verification of Identity during Remote Assessments and Individual Personalized Interactions

Authentication is one of the most important aspects of the present society. Almost everything people do has a technological aspect. If systems are not implemented correctly and safely, namely by access control via authentication, several aspects of (cyber)security and privacy can be exploited by ill-intentioned people. Unauthorised access can be made in multiple ways, pretending to be another user is one of them. This dissertation aims at the creation of a system prototype that can verify if the logged-in user is the actual person using the system. This is achieved utilising behavioural biometrics, such has keyboard and mouse dynamics, to collect interactions with the system and machine learning to predict if the collected information matches the person one says to be. In case the algorithm detects an anomaly, the computer locks itself, so that only authorised people with true access to the computer can re-log in.A Autenticação é um dos aspetos mais importantes da sociedade atual. Quase todas as ações concretizadas pelas pessoas que a compõem têm um aspeto tecnológico. Caso os sistemas não sejam implementados segura e corretamente, nomeadamente através do controlo de acesso via autenticação, vários aspetos de (ciber)segurança e privacidade podem ser violados por pessoas mal intencionadas. Este acesso pode dar-se de muitas formas, sendo uma delas fazendo-se passar por um outro utilizador. Esta dissertação visa a criação de um protótipo de sistema que consiga verificar a identidade do utilizador autenticado no sistema. Esta verificação será concretizada através da análise de biométricas comportamentais, neste caso, dinâmicas de rato e teclado, para realizar a coleta de interações com o sistema e aprendizagem automática para prever, através da informação coletada, se esta corresponde à pessoa autenticada. Caso o algoritmo detete uma anomalia, o computador irá bloquear, de modo a que apenas pessoas autorizadas consigam fazer uma reautenticação

Face modeling for face recognition in the wild.

Face understanding is considered one of the most important topics in computer vision field since the face is a rich source of information in social interaction. Not only does the face provide information about the identity of people, but also of their membership in broad demographic categories (including sex, race, and age), and about their current emotional state. Facial landmarks extraction is the corner stone in the success of different facial analyses and understanding applications. In this dissertation, a novel facial modeling is designed for facial landmarks detection in unconstrained real life environment from different image modalities including infra-red and visible images. In the proposed facial landmarks detector, a part based model is incorporated with holistic face information. In the part based model, the face is modeled by the appearance of different face part(e.g., right eye, left eye, left eyebrow, nose, mouth) and their geometric relation. The appearance is described by a novel feature referred to as pixel difference feature. This representation is three times faster than the state-of-art in feature representation. On the other hand, to model the geometric relation between the face parts, the complex Bingham distribution is adapted from the statistical community into computer vision for modeling the geometric relationship between the facial elements. The global information is incorporated with the local part model using a regression model. The model results outperform the state-of-art in detecting facial landmarks. The proposed facial landmark detector is tested in two computer vision problems: boosting the performance of face detectors by rejecting pseudo faces and camera steering in multi-camera network. To highlight the applicability of the proposed model for different image modalities, it has been studied in two face understanding applications which are face recognition from visible images and physiological measurements for autistic individuals from thermal images. Recognizing identities from faces under different poses, expressions and lighting conditions from a complex background is an still unsolved problem even with accurate detection of landmark. Therefore, a learning similarity measure is proposed. The proposed measure responds only to the difference in identities and filter illuminations and pose variations. similarity measure makes use of statistical inference in the image plane. Additionally, the pose challenge is tackled by two new approaches: assigning different weights for different face part based on their visibility in image plane at different pose angles and synthesizing virtual facial images for each subject at different poses from single frontal image. The proposed framework is demonstrated to be competitive with top performing state-of-art methods which is evaluated on standard benchmarks in face recognition in the wild. The other framework for the face understanding application, which is a physiological measures for autistic individual from infra-red images. In this framework, accurate detecting and tracking Superficial Temporal Arteria (STA) while the subject is moving, playing, and interacting in social communication is a must. It is very challenging to track and detect STA since the appearance of the STA region changes over time and it is not discriminative enough from other areas in face region. A novel concept in detection, called supporter collaboration, is introduced. In support collaboration, the STA is detected and tracked with the help of face landmarks and geometric constraint. This research advanced the field of the emotion recognition

The Impact Of The Development Of ICT In Several Hungarian Economic Sectors

As the author could not find a reassuring mathematical and statistical method in the literature for studying the effect of information communication technology on enterprises, the author suggested a new research and analysis method that he also used to study the Hungarian economic sectors. The question of what factors have an effect on their net income is vital for enterprises. At first, the author studied some potential indicators related to economic sectors, then those indicators were compared to the net income of the surveyed enterprises. The resulting data showed that the growing penetration of electronic marketplaces contributed to the change of the net income of enterprises to the greatest extent. Furthermore, among all the potential indicators, it was the only indicator directly influencing the net income of enterprises. With the help of the compound indicator and the financial data of the studied economic sectors, the author made an attempt to find a connection between the development level of ICT and profitability. Profitability and productivity are influenced by a lot of other factors as well. As the effect of the other factors could not be measured, the results – shown in a coordinate system - are not full but informative. The highest increment of specific Gross Value Added was produced by the fields of ‘Manufacturing’, ‘Electricity, gas and water supply’, ‘Transport, storage and communication’ and ‘Financial intermediation’. With the exception of ‘Electricity, gas and water supply’, the other economic sectors belong to the group of underdeveloped branches (below 50 percent). On the other hand, ‘Construction’, ‘Health and social work’ and ‘Hotels and restaurants’ can be seen as laggards, so they got into the lower left part of the coordinate system. ‘Agriculture, hunting and forestry’ can also be classified as a laggard economic sector, but as the effect of the compound indicator on the increment of Gross Value Added was less significant, it can be found in the upper left part of the coordinate system. Drawing a trend line on the points, it can be made clear that it shows a positive gradient, that is, the higher the usage of ICT devices, the higher improvement can be detected in the specific Gross Value Added

ENABLING IOT AUTHENTICATION, PRIVACY AND SECURITY VIA BLOCKCHAIN

Although low-power and Internet-connected gadgets and sensors are increasingly integrated into our lives, the optimal design of these systems remains an issue. In particular, authentication, privacy, security, and performance are critical success factors. Furthermore, with emerging research areas such as autonomous cars, advanced manufacturing, smart cities, and building, usage of the Internet of Things (IoT) devices is expected to skyrocket. A single compromised node can be turned into a malicious one that brings down whole systems or causes disasters in safety-critical applications. This dissertation addresses the critical problems of (i) device management, (ii) data management, and (iii) service management in IoT systems. In particular, we propose an integrated platform solution for IoT device authentication, data privacy, and service security via blockchain-based smart contracts. We ensure IoT device authentication by blockchain-based IC traceability system, from its fabrication to its end-of-life, allowing both the supplier and a potential customer to verify an IC’s provenance. Results show that our proposed consortium blockchain framework implementation in Hyperledger Fabric for IC traceability achieves a throughput of 35 transactions per second (tps). To corroborate the blockchain information, we authenticate the IC securely and uniquely with an embedded Physically Unclonable Function (PUF). For reliable Weak PUF-based authentication, our proposed accelerated aging technique reduces the cumulative burn-in cost by ∼ 56%. We also propose a blockchain-based solution to integrate the privacy of data generated from the IoT devices by giving users control of their privacy. The smart contract controlled trust-base ensures that the users have private access to their IoT devices and data. We then propose a remote configuration of IC features via smart contracts, where an IC can be programmed repeatedly and securely. This programmability will enable users to upgrade IC features or rent upgraded IC features for a fixed period after users have purchased the IC. We tailor the hardware to meet the blockchain performance. Our on-die hardware module design enforces the hardware configuration’s secure execution and uses only 2,844 slices in the Xilinx Zedboard Zynq Evaluation board. The blockchain framework facilitates decentralized IoT, where interacting devices are empowered to execute digital contracts autonomously

Building the Infrastructure for Cloud Security

Computer scienc

State of the Art in Face Recognition

Notwithstanding the tremendous effort to solve the face recognition problem, it is not possible yet to design a face recognition system with a potential close to human performance. New computer vision and pattern recognition approaches need to be investigated. Even new knowledge and perspectives from different fields like, psychology and neuroscience must be incorporated into the current field of face recognition to design a robust face recognition system. Indeed, many more efforts are required to end up with a human like face recognition system. This book tries to make an effort to reduce the gap between the previous face recognition research state and the future state

Challenges in Cybersecurity and Privacy - the European Research Landscape

Cybersecurity and Privacy issues are becoming an important barrier for a trusted and dependable global digital society development. Cyber-criminals are continuously shifting their cyber-attacks specially against cyber-physical systems and IoT, since they present additional vulnerabilities due to their constrained capabilities, their unattended nature and the usage of potential untrustworthiness components. Likewise, identity-theft, fraud, personal data leakages, and other related cyber-crimes are continuously evolving, causing important damages and privacy problems for European citizens in both virtual and physical scenarios. In this context, new holistic approaches, methodologies, techniques and tools are needed to cope with those issues, and mitigate cyberattacks, by employing novel cyber-situational awareness frameworks, risk analysis and modeling, threat intelligent systems, cyber-threat information sharing methods, advanced big-data analysis techniques as well as exploiting the benefits from latest technologies such as SDN/NFV and Cloud systems. In addition, novel privacy-preserving techniques, and crypto-privacy mechanisms, identity and eID management systems, trust services, and recommendations are needed to protect citizens’ privacy while keeping usability levels. The European Commission is addressing the challenge through different means, including the Horizon 2020 Research and Innovation program, thereby financing innovative projects that can cope with the increasing cyberthreat landscape. This book introduces several cybersecurity and privacy research challenges and how they are being addressed in the scope of 15 European research projects. Each chapter is dedicated to a different funded European Research project, which aims to cope with digital security and privacy aspects, risks, threats and cybersecurity issues from a different perspective. Each chapter includes the project’s overviews and objectives, the particular challenges they are covering, research achievements on security and privacy, as well as the techniques, outcomes, and evaluations accomplished in the scope of the EU project. The book is the result of a collaborative effort among relative ongoing European Research projects in the field of privacy and security as well as related cybersecurity fields, and it is intended to explain how these projects meet the main cybersecurity and privacy challenges faced in Europe. Namely, the EU projects analyzed in the book are: ANASTACIA, SAINT, YAKSHA, FORTIKA, CYBECO, SISSDEN, CIPSEC, CS-AWARE. RED-Alert, Truessec.eu. ARIES, LIGHTest, CREDENTIAL, FutureTrust, LEPS. Challenges in Cybersecurity and Privacy - the European Research Landscape is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science and communications networks interested in learning about cyber-security and privacy aspects

Electronic Imaging & the Visual Arts. EVA 2013 Florence

Important Information Technology topics are presented: multimedia systems, data-bases, protection of data, access to the content. Particular reference is reserved to digital images (2D, 3D) regarding Cultural Institutions (Museums, Libraries, Palace – Monuments, Archaeological Sites). The main parts of the Conference Proceedings regard: Strategic Issues, EC Projects and Related Networks & Initiatives, International Forum on “Culture & Technology”, 2D – 3D Technologies & Applications, Virtual Galleries – Museums and Related Initiatives, Access to the Culture Information. Three Workshops are related to: International Cooperation, Innovation and Enterprise, Creative Industries and Cultural Tourism