Magaña Lizarrondo, Eduardo

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https://academica-e.unavarra.es/handle/2454/49486

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Magaña Lizarrondo

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Eduardo

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Ingeniería Eléctrica, Electrónica y de Comunicación

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ISC. Institute of Smart Cities

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0000-0002-6851-3414

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88546

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2199

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2018 - 20192
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Author: Izal Azcárate, Mikel × Subject: Monitoring ×

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    PublicationOpen Access
    Ransomware encrypted your files but you restored them from network traffic
    (IEEE, 2019) Berrueta Irigoyen, Eduardo; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
    In a scenario where user files are stored in a network shared volume, a single computer infected by ransomware could encrypt the whole set of shared files, with a large impact on user productivity. On the other hand, medium and large companies maintain hardware or software probes that monitor the traffic in critical network links, in order to evaluate service performance, detect security breaches, account for network or service usage, etc. In this paper we suggest using the monitoring capabilities in one of these tools in order to keep a trace of the traffic between the users and the file server. Once the ransomware is detected, the lost files can be recovered from the traffic trace. This includes any user modifications posterior to the last snapshot of periodic backups. The paper explains the problems faced by the monitoring tool, which is neither the client nor the server of the file sharing operations. It also describes the data structures in order to process the actions of users that could be simultaneously working on the same file. A proof of concept software implementation was capable of successfully recovering the files encrypted by 18 different ransomware families.
  • Thumbnail Image
    PublicationOpen Access
    Computation of traffic time series for large populations of IoT devices
    (MDPI, 2018) Izal Azcárate, Mikel; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; García-Jiménez, Santiago; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
    En este artículo se estudian las tecnicas para clasificar paquetes de tráfico de red en múltiples clases orientadas a la realización de series temporales de tráfico en escenarios de un elevado numero de clases como pueden ser los proveedores de red para dispositivos IoT. Se muestra que usando técnicas basadas en DStries se pueden monitorizar en tiempo real redes con decenas de miles de dispositivos.