Non INESC TEC publications - Book Chapters

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    On the feasibility of byzantine agreement to secure fog/edge data management
    ( 2021) Houssam Ahmad Yactin ; Shoker,A ; 6717
    Fog/Edge computing improves the latency and security of data by keeping storage and computation close to the data source. Nevertheless, this raises other security challenges against malicious, a.k.a, Byzantine, attacks that can exploit the isolation of nodes, or when access to distributed data is required in untrusted environments. In this work, we study the feasibility of deploying Byzantine Agreement protocols to improve the security of fog/edge systems in untrusted environments. In particular, we explore existing Byzantine Agreement protocols, heavily developed in the Blockchain area, emphasizing the Consistency, Availability, and Partition-Tolerance tradeoffs in a geo-replicated system. Our work identifies and discusses three different approaches that follow the Strong Consistency, Eventual Consistency, and Strong Eventual Consistency models. Our conclusions show that Byzantine Agreement protocols are still immature to be used by fog/edge computing in untrusted environment due to their high finality latency; however, they are promising candidates that encourage further research in this direction. © 2021, Springer Nature Switzerland AG.
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    Cyst Detection in OCT Images for Pathology Characterization
    ( 2014) González,A ; Beatriz Remeseiro López ; Ortega,M ; Penedo,M ; Charlón,P
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    Machine Learning Applied to Optometry Data
    ( 2018) Beatriz Remeseiro López ; Barreira,N ; Sánchez Brea,L ; Ramos,L ; Mosquera,A
    Optometry is the primary health care of the eye and visual system. It involves detecting defects in vision, signs of injury, ocular diseases as well as problems with general health that produce side effects in the eyes. Myopia, presbyopia, glaucoma or diabetic retinopathy are some examples of conditions that optometrists usually diagnose and treat. Moreover, there is another condition that we have all experienced once in a while, especially if we work with computers or have been exposed to smoke or wind. Dry eye syndrome (DES) is a hidden multifactorial disease related with the quality and quantity of tears. It causes discomfort and could lead to severe visual problems. In this chapter, we explain how machine learning techniques can be applied in some DES medical tests in order to produce an objective, repeatable and automatic diagnosis. The results of our experiments show that the proposed methodologies behave like the experts so that they can be applied in the daily practice. © Springer International Publishing AG 2018.
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    Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition
    ( 2015) Adrian Galdran ; Picón,A ; Garrote,E ; Pardo,D
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    A Variational Framework for Single Image Dehazing
    ( 2015) Adrian Galdran ; Vazquez-Corral,J ; Pardo,D ; Bertalmío,M