Towards more Secure and Efficient Password Databases

Password databases form one of the backbones of nowadays web applications. Every web application needs to store its users’ credentials (email and password) in an efficient way, and in popular applications (Google, Facebook, Twitter, etc.) these databases can grow to store millions of user credentials simultaneously. However, despite their critical nature and susceptibility to targeted attacks, the techniques used for securing password databases are still very rudimentary, opening the way to devastating attacks. Just in the year of 2016, and as far as publicly disclosed, there were more than 500 million passwords stolen in internet hacking attacks. To solve this problem we commit to study several schemes like property-preserving encryption schemes (e.g. deterministic encryption), encrypted data-structures that support operations (e.g. searchable encryption), partially homomorphic encryption schemes, and commodity trusted hardware (e.g. TPM and Intel SGX). In this thesis we propose to make a summary of the most efficient and secure techniques for password database management systems that exist today and recreating them to accommodate a new and simple universal API. We also propose SSPM(Simple Secure Password Management), a new password database scheme that simultaneously improves efficiency and security of current solutions existing in literature. SSPM is based on Searchable Symmetric Encryption techniques, more specifically ciphered data structures, that allow efficient queries with the minimum leak of access patterns. SSPM adapts these structures to work with the necessary operation of password database schemes preserving the security guarantees. Furthermore, SSPM explores the use of trusted hardware to minimize the revelation of access patterns during the execution of operations and protecting the storage of cryptographic keys. Experimental results with real password databases shows us that SSPM has a similar performance compared with the solutions used today in the industry, while simultaneous increasing the offered security conditions

Does the age of entry in primary school affect student’s achievement?

The school starting age is one the factors that influence student’s educational attainment. Using a large dataset containing information of students from public schools in Portugal, it was possible to establish a positive relation between the entry age and educational outcomes, such as retentions and exam’s grades. However, deferring a child’s entry by one year does not seem to provide large benefits for students. This paper complements the analysis by understanding the main characteristics that lead to child’s deferment and reinforces the idea that educational policy is a complex issue for Governments to deal with

Clear-water scour at single piers and pile groups

The major damage to bridges at river crossings occurs during floods. Damage is caused for various reasons, one of the main reasons being the riverbed scour at bridge foundations. Local scour is induced by the flow field generated around piers typically inserted in movable bed rivers. In Portugal, the tragic accident of Entre-os-Rios was mostly due to scour at one of the bridge piers. Physical and economic reasons lead to bridge foundations composed of a pier column founded on a pile cap, supported by an array of piles. Piers of this configuration are known as complex piers. Frequently the pile cap is completely buried, or in opposition, above the water, being the column or the pile group respectively the only structural element interacting with the flow and causing local scour. In modern bridges it is also common to find structural solutions where the deck is supported directly by pile groups composed of only one alignment, without pile cap. For scouring proposes the structural elements may be considered as single piers, pile groups and pier alignments. The construction of new bridges and the maintenance of thousands of bridges built before the main developments in local scour prediction, amount to costs of billions of Euro and justifies a rigorous prediction of the scour depth, both for economic and safety of human lives reasons. The present study develops an extensive research to systematically map equilibrium scour at single cylindrical piers and pile groups and relate the observations with the characteristic variables of the tests. Special attention is given to the effect of time, relative sediment size and relative approach flow depth at single cylindrical piers and spacing, skew-angle, number of columns and time at pile groups. The pertinence of considering the effect of viscosity it is also assessed. Using dimensional analysis, the following major conclusions are achieved. Regarding single cylindrical piers, it is discussed the required duration of the laboratory tests to render reliable equilibrium scour depths and it is confirmed that equilibrium scour depth decreases with the relative sediment size. It is suggested a predictor for the equilibrium scour depth at single cylindrical piers, function of relative sediment size and relative approach flow depth. The parameters of the equation suggested by Franzetti et al. (1982) are fully characterized rendering a predictor of the scour depth time evolution. Regarding pile groups and pier alignments, it is assessed the effect of the test duration on the equilibrium scour depth and it is confirmed that the spacing factor and the factor for the number of aligned rows recommended in the predictors commonly used in engineering practice are reliable since the scour depth at single cylindrical piers and pile groups remain essentially self-similar in time. The prediction of the equilibrium scour depth at pile groups is improved by the suggestion of a aggregate pile group factor, function of the pile spacing, skew-angle and number of parallel pile alignments. Finally it is revealed that the viscosity may affect scouring in laboratory tests

Automatic driving: 2D detection and tracking using artificial intelligence techniques

Dissertação de mestrado integrado em Informatics EngineeringRoad accidents are estimated to be the cause of millions of deaths and tens of millions of injuries every year. For this reason, any measure that reduces accidents' probability or severity will save lives. Speeding, driving under the influence of psychotropic substances and distraction are leading causes of road accidents. Causes that can be classified as human since they all come from driver errors. Autonomous driving is a potential solution to this problem as it can reduce road accidents by removing human error from the task of driving. This dissertation aims to study Artificial Intelligence techniques and Edge Computing networks to explore solutions for autonomous driving. To this end, Artificial Intelligence models for detecting and tracking objects based on Machine Learning and Computer Vision, and Edge Computing networks for vehicles were explored. The YOLOv5 model was studied for object detection, in which different training parameters and data pre-processing techniques were applied. For object tracking, the StrongSORT model was chosen, for which its performance was evaluated for different combinations of its components. Finally, the Simu5G simulation tool was studied in order to simulate an edge computing network, and the viability of this type of network to aid autonomous driving was analysed.É estimado que os acidentes rodoviários sejam a causa de milhões de mortes e dezenas de milhões de lesões todos os anos. Por esta razão, qualquer medida que diminua a probabilidade de acidentes ou que diminua a sua gravidade acabará por salvar vidas. Excesso de velocidade, condução sob influência de substâncias psicotrópicas e distração no ato da condução são algumas das principais causas de acidentes rodoviários. Causas essas que podem ser classificadas como humanas visto que são oriundas de um erro do condutor. A condução autónoma surge como solução para este problema. Esta tem o potencial de diminuir acidentes rodoviários removendo o erro humano da tarefa da condução. Esta dissertação teve como objetivo o estudo de técnicas Inteligência Artificial e redes Computação de Borda de forma a explorar soluções para a condução autónoma. Para tal foram estuados modelos Inteligência Artificial de deteção e rastreamento de objetos com base nas áreas de Aprendizagem Máquina e Visão por Computador e redes de Computação de Borda para veículos. Para a deteção de objetos foi estudado o modelo YOLOv5, no qual diferentes combinações de parâmetros de treino e técnicas de pré-processamento de dados foram aplicadas. Para o rastreamento de objetos foi escolhido o modelo StrongSORT, para o qual foi avaliada a sua performance para diferentes combinações das suas componentes. Por fim, foi estudada a ferramenta de simulação Simu5G, de forma a simular uma rede de computação de borda, e foi feita uma análise sobre a viabilidade deste tipo de redes no auxílio à condução autónoma

A sudden death prevention system for babies

The growth of the smartphones market share has driven the entry of a large number of new opportunities to launch new applications/mobile tools both by companies but also by individuals’ entities. The prototype solution presented here fits in the increasing emerging of smartphones applications for the health sector. This dissertation presents a solution to prevent a sudden infant death syndrome. It includes biofeedback monitoring of babies, using body sensors to collect data that will be presented in two different mobile applications: the Main Application and the Client Application. Breathing, temperature, position, and heart rate are used, and placed to the baby’s body. The Main Application will receive the data collected by the sensors via Bluetooth. This contains a monitoring tool, which parses and transforms raw data to be readable and understandable for users. This application will send the data to a Web service to be stored in a database that supports the entire created solution. The Client Application will consume the data stored in the database every previous second. Both applications have an important functionality that allows the trigger of alert notifications when an error occurs with the data collected by the sensors and the caregiver is informed with an alert in a short time. This document describes in detail the whole process done to deploy a prototype that demonstrates and validates the proposed solution and is ready for use

Model-driven Personalisation of Human-Computer Interaction across Ubiquitous Computing Applications

Personalisation is essential to Ubiquitous Computing (Ubicomp), which focuses on a human-centred paradigm aiming to provide interaction with adaptive content, services, and interfaces towards each one of its users, according to the context of the applications’ scenarios. However, the provision of that appropriated personalised interaction is a true challenge due to different reasons, such as the user interests, heterogeneous environments and devices, dynamic user behaviour and data capture. This dissertation focuses on a model-driven personalisation solution that has the main goal of facili-tating the implementation of a personalised human-computer interaction across different Ubicomp scenarios and applications. The research reported here investigates how a generic and interoperable model for personalisation can be used, shared and processed by different applications, among diverse devices, and across different scenarios, studying how it can enrich human-computer interaction. The research started by the definition of a consistent user model with the integration of context to end in a pervasive model for the definition of personalisations across different applications. Besides the model proposal, the other key contributions within the solution are the modelling frame-work, which encapsulates the model and integrates the user profiling module, and a cloud-based platform to pervasively support developers in the implementation of personalisation across different applications and scenarios. This platform provides tools to put end users in control of their data and to support developers through web services based operations implemented on top of a personalisa-tion API, which can also be used independently of the platform for testing purposes, for instance. Several Ubicomp applications prototypes were designed and used to evaluate, at different phases, both the solution as a whole and each one of its components. Some were specially created with the goal of evaluating specific research questions of this work. Others were being developed with a pur-pose other than for personalisation evaluation, but they ended up as personalised prototypes to better address their initial goals. The process of applying the personalisation model to the design of the latter should also work as a proof of concept on the developer side. On the one hand, developers have been probed with the implementation of personalised applications using the proposed solution, or a part of it, to assess how it works and can help them. The usage of our solution by developers was also important to assess how the model and the platform respond to the developers’ needs. On the other hand, some prototypes that implement our model-driven per-sonalisation solution have been selected for end user evaluation. Usually, user testing was conducted at two different stages of the development, using: (1) a non-personalised version; (2) the final per-sonalised version. This procedure allowed us to assess if personalisation improved the human-com-puter interaction. The first stage was also important to know who were the end users and gather interaction data to come up with personalisation proposals for each prototype. Globally, the results of both developers and end users tests were very positive. Finally, this dissertation proposes further work, which is already ongoing, related to the study of a methodology to the implementation and evaluation of personalised applications, supported by the development of three mobile health applications for rehabilitation