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Proceedings Paper

Attack detection in unattended sensor networks
Author(s): Curt Wu; Camille Monnier; Gerald Fry; Lewis Girod; Jahn Luke
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Paper Abstract

Because sensor networks are often deployed in hostile environments where their security and integrity may be compromised, it is essential to maximize the reliability and trustworthiness of existing and envisioned sensor networks. During operations, the sensor network must be robust to deception, node compromise, and various other attacks, while maintaining the operator's situational awareness regarding the health and integrity of the system. To address these needs, we have designed a Framework to Ensure and Assess Trustworthiness in Sensor systems (FEATS) to identify attacks on sensor system integrity and inform the operator of sensor data trustworthiness. We have developed and validated unsupervised anomaly detection algorithms for sensor data captured from an experimental acoustic sensor platform under a number of attack scenarios. The platform, which contains four audio microphones, was exposed to two physical attacks (audio filtering and audio playback) as well as a live replay attack (replaying live audio data that is captured at a remote location), which is analogous to a wormhole attack in the routing layer. With our unsupervised learning algorithms, we were able to successfully identify the presence of various attacks.

Paper Details

Date Published: 28 April 2010
PDF: 10 pages
Proc. SPIE 7709, Cyber Security, Situation Management, and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, 770908 (28 April 2010); doi: 10.1117/12.852681
Show Author Affiliations
Curt Wu, Charles River Analytics, Inc. (United States)
Camille Monnier, Charles River Analytics, Inc. (United States)
Gerald Fry, Charles River Analytics, Inc. (United States)
Lewis Girod, Massachusetts Institute of Technology (United States)
Jahn Luke, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 7709:
Cyber Security, Situation Management, and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II
William J. Tolone; John F. Buford; William Ribarsky; Gabriel Jakobson; John Erickson, Editor(s)

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