Recent Submissions

  • Epicentral region estimation using convolutional neural networks 

    Cruz de la Cruz, Stalin Leonel; Tous Liesa, Rubén; Otero Calviño, Beatriz; Alvarado Bermúdez, Leonardo; Mus León, Sergi; Rojas Ulacio, Otilio Jose (Springer Nature, 2022)
    Conference report
    Restricted access - publisher's policy
    Recent works have assessed the capability of deep neural networks of estimating the epicentral source region of a seismic event from a single-station three-channel signal. In all the cases, the geographical partitioning ...
  • Malicious website detection through deep learning algorithms 

    Gutiérrez Escobar, Norma; Otero Calviño, Beatriz; Rodríguez Luna, Eva; Canal Corretger, Ramon (Springer Nature, 2022)
    Conference report
    Restricted access - publisher's policy
    Traditional methods that detect malicious websites, such as blacklists, do not update frequently, and they cannot detect new attackers. A system capable of detecting malicious activity using Deep Learning (DL) has been ...
  • Deep learning detection of GPS spoofing 

    Jullian Parra, Olivia; Otero Calviño, Beatriz; Stojilovic, Mirjana; Costa Prats, Juan José; Verdú Mulà, Javier; Pajuelo González, Manuel Alejandro (Springer Nature, 2022)
    Conference report
    Restricted access - publisher's policy
    Unmanned aerial vehicles (UAVs) are widely deployed in air navigation, where numerous applications use them for safety-of-life and positioning, navigation, and timing tasks. Consequently, GPS spoofing attacks are more and ...
  • SRAM arrays with built-in parity computation for real-time error detection in cache tag arrays 

    Canal Corretger, Ramon; Sazeides, Yiannakis; Bramnik, Arkady (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Conference report
    Open Access
    This work proposes an SRAM array with built-in real-time error detection (RTD) capabilities. Each cell in the new RTD-SRAM array computes its part of the real-time parity of an SRAM array column on-the-fly. RTD based arrays ...
  • 2D error correction for F/F based arrays using in-situ Real-Time Error Detection (RTD) 

    Sazeides, Yiannakis; Bramnik, Arkady; Gabor, Ron; Nicopoulos, Chrysostomos; Canal Corretger, Ramon; Konstantinou, Dimitris; Dimitrakopoulos, Giorgos (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Conference lecture
    Open Access
    This work proposes in-situ Real-Time Error Detection (RTD): embedding hardware in a memory array for detecting a fault in the array when it occurs, rather than when it is read. RTD breaks the serialization between data ...
  • Random forest parameterization for earthquake catalog generation 

    Llácer Giner, David; Otero Calviño, Beatriz; Tous Liesa, Rubén; Monterrubio Velasco, Marisol; Carrasco Jiménez, José; Rojas Ulacio, Otilio (Springer, 2020)
    Conference report
    Open Access
    An earthquake is the vibration pattern of the Earth’s crust induced by the sliding of geological faults. They are usually recorded for later studies. However, strong earthquakes are rare, small-magnitude events may pass ...
  • Privacy preserving deep learning framework in fog computing 

    Gutiérrez Escobar, Norma; Rodríguez Luna, Eva; Mus León, Sergi; Otero Calviño, Beatriz; Canal Corretger, Ramon (Springer, 2020)
    Conference report
    Open Access
    Nowadays, the widespread use of mobile devices has raised serious cybersecurity challenges. Mobile services and applications use deep learning (DL) models for the modelling, classification and recognition of complex data, ...
  • Lightweight protection of cryptographic hardware accelerators against differential fault analysis 

    Lasheras Mas, Ana; Canal Corretger, Ramon; Rodríguez Luna, Eva; Cassano, Luca (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Conference report
    Open Access
    Hardware acceleration circuits for cryptographic algorithms are largely deployed in a wide range of products. The HW implementations of such algorithms often suffer from a number of vulnerabilities that expose systems to ...
  • Long short-term memory networks for earthquake detection in Venezuelan regions 

    Mus León, Sergi; Gutiérrez Escobar, Norma; Tous Liesa, Rubén; Otero Calviño, Beatriz; Cruz de la Cruz, Stalin Leonel; Llácer Giner, David; Alvarado Bermúdez, Leonardo; Rojas, Otilio (Springer, 2019)
    Conference lecture
    Open Access
    Reliable earthquake detection and location algorithms are necessary to properly catalog and analyze the continuously growing seismic records. This paper reports the results of applying Long Short-Term Memory (LSTM) networks ...
  • Protecting RSA hardware accelerators against differential fault analysis through residue checking 

    Lasheras Mas, Ana; Canal Corretger, Ramon; Rodríguez Luna, Eva; Cassano, Luca (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Conference report
    Open Access
    Hardware accelerators for cryptographic algorithms are ubiquitously deployed in nowadays consumer and industrial products. Unfortunately, the HW implementations of such algorithms often suffer from vulnerabilities that ...
  • Challenges in deeply heterogeneous high performance systems 

    Agosta, Giovanni; Fornaciari, William; Atienza, David; Canal Corretger, Ramon; Cilardo, Alessandro; Flich Cardo, José; Hernández Luz, Carles; Kulczewski, Michal; Massari, Giuseppe; Tornero Gavilá, Rafael; Zapater Sancho, Marina (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Conference report
    Open Access
    RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring ...
  • Modem gain-cell memories in advanced technologies 

    Amat Bertran, Esteve; Canal Corretger, Ramon; Rubio Sola, Jose Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Conference report
    Open Access
    With the advent of the slowdown in DRAM capacitor scaling [1] and the increased reliability problems of traditional 6T SRAM memories [2], industry and academia have looked for alternative memory cells. Among those, gain- ...

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