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RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks. | LitMetric

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

Sensors (Basel)

Department of Computer Engineering, School of Electronics and Information, Kyung Hee University, Korea; E-Mails: (S.O.A.); (M.S.S.); (S.-W.L.).

Published: September 2012

AI Article Synopsis

  • The IP-based Ubiquitous Sensor Network (IP-USN) aims to integrate everyday devices into the Internet of Things using existing IP technologies.
  • Security is a major concern for researchers focusing on how to protect these networks from intrusions, which is crucial for future market needs.
  • The paper introduces RIDES, a hybrid Intrusion Detection System that combines signature-based and anomaly-based detection methods, including a unique attack-signature identifier and a statistical process control technique known as CUSUM charts.

Article Abstract

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297149PMC
http://dx.doi.org/10.3390/s90503447DOI Listing

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