PUE Attack Detection in CWSN Using Collaboration and Learning Behavior
Posted on by jblesa

Title: PUE Attack Detection in CWSN Using Collaboration and Learning Behavior
Authors: Javier Blesa, Elena Romero, Alba Rozas, Alvaro Araujo and Octavio Nieto-Taladriz
Published in: International Journal of Distributed Sensor Networks
Date of Publication: June 2013
Digital Object Identifier : 10.1155/2013/815959
Web: http://www.hindawi.com/journals/ijdsn/2013/815959/

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

cognitive radio module

 

PUE attack detection in CWSNs using anomaly detection techniques
Posted on by jblesa

Title: PUE attack detection in CWSNs using anomaly detection techniques
Authors: Javier Blesa, Elena Romero, Alba Rozas and Alvaro Araujo
Published in: EURASIP Journal on Wireless Communications and Networking 
Date of Publication: September 2013
Digital Object Identifier : 10.1186/1687-1499-2013-215
Web: http://jwcn.eurasipjournals.com/content/2013/1/215

Cognitive wireless sensor network (CWSN) is a new paradigm, integrating cognitive features in traditional wireless sensor networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in cognitive wireless sensor networks is an important problem since these kinds of networks manage critical applications and data. The specific constraints of WSN make the problem even more critical, and effective solutions have not yet been implemented. Primary user emulation (PUE) attack is the most studied specific attack deriving from new cognitive features. This work discusses a new approach, based on anomaly behavior detection and collaboration, to detect the primary user emulation attack in CWSN scenarios. Two non-parametric algorithms, suitable for low-resource networks like CWSNs, have been used in this work: the cumulative sum and data clustering algorithms. The comparison is based on some characteristics such as detection delay, learning time, scalability, resources, and scenario dependency. The algorithms have been tested using a cognitive simulator that provides important results in this area. Both algorithms have shown to be valid in order to detect PUE attacks, reaching a detection rate of 99% and less than 1% of false positives using collaboration.

clusters

 

Puentes – Low cost bridge health monitoring by ambient vibration tests using wireless sensors
Posted on by frta

puentesMeasurebox

The proposed research project is aimed to develop and implement a system for damage detection and localization in bridge structures. This structural health monitoring system is based on ambient dynamic tests, i.e. tests subjected to uncontrolled loading (traffic, wind etc.), and on the application of advanced structural identification techniques. The tests are carried out in such a way that existing bridge traffic remains undisturbed. The structural health monitoring system is automated to integrate the different measurement phases:

  1. positioning of sensors,
  2. data acquisition,
  3. deduction of dynamic structural characteristics and,
  4. evaluation of the structural behaviour.

The measurement campaign can be carried out by a reduced technical team in a relatively short time. In this context different bridge tests can be considered: bridges without accessible design, with a preliminary design, with an updated design and with results from a previous ambient dynamic test. Existing algorithms and related software will be upgraded in view of automatic design of low cost sensor distribution and damage localization from the test output data. The developed system will be applied to two pilot bridges to check the quality level of the derived damage information. The structural health monitoring system will be tailored to the common bridge types: simply supported or continuous, in reinforced or prestressed concrete. Finally, in order to evaluate the efficiency of the low cost wireless sensor system, a comparison will be made with a traditional wired system, regarding feasibility and cost effectiveness.

Visit the web page of the project for more information

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RS – Rehabilitación Sostenible de edificios
Posted on by b105
  • Title: Rehabilitación Sostenible de edificios (RS)rs
  • Funding Organization: FCC via Centro para el Desarrollo Tecnológico Industrial (CDTI) – Ministerio de Ciencia e Innovación
  • Participants:
    • Companies: FCC, URSA, METALES EXTRUIDOS, ENERGESIS and OPLAN.
    • Research Centers: Universidad de Málaga (UM), Universidad de Sevilla (US), Universidad Politécnica de Madrid (UPM) and Instituto Eduardo Torroja.
  • Description: The main objective of the RS project is the development of an integrated system to achieve an improvement in energy efficiency in the sustainable rehabilitation of existing buildings. Related topics are smart power management, thermal control and renewable energy systems. LSI-B105 at UPM is in charge of monitoring power consumption and temperature at home, gathering user data and preferences and designing energy-efficient strategies for warming the different rooms.

RS_process

LINEO: Sistema de Localización de personal basado en tenologías interactivas para su aplicación en entornos de obra
Posted on by b105
logologoMINECOlogoFEDER

lineo

  • Title: Sistema de Localización de personal basado en tenologías interactivas para su aplicación en entornos de obra
  • Funding Organisation: Ministerio de Ciencia e Innovación
  • Participants: Dragados S.A., SICE, Universidad de Valencia, Universidad Politécnica de Madrid
  • Description: Reduce workplace accidents in construction, unfortunately too common, due to collisions or violations produced by large machinery that interacts in many moments with workers on foot moving nearby. LINEO location system must provide real-time measurements (time sub-second update), high accuracy (less than 1 meter) and with great robustness and reliability in aggressive external environment and unstructured.

lineoImagen