Main Reference PaperSegment-Based Anomaly Detection with Approximated Sample Covariance Matrix in Wireless Sensor Networks, IEEE Transactions on Parallel and Distributed Systems, February 2015.
  • To detect the long term anomalies in sensor network, this work propose a technique called as segment-based anomaly detection. To identify the anomalies by measuring the minimum prediction variance of each data segment and, if a data segment is distinct in terms of its prediction variance, it is identified as an anomaly.

+ Description
  • To detect the long term anomalies in sensor network, this work propose a technique called as segment-based anomaly detection. To identify the anomalies by measuring the minimum prediction variance of each data segment and, if a data segment is distinct in terms of its prediction variance, it is identified as an anomaly.

  • To detect the long term anomalies.

  • Reducing communication and computation cost

+ Aim & Objectives
  • To detect the long term anomalies.

  • Reducing communication and computation cost

  • An effective technique is contributed to prevent the anomalies in sensor network.

+ Contribution
  • An effective technique is contributed to prevent the anomalies in sensor network.

  • OS : Window 7 (Cygwin) / Ubuntu 12.04 LTS 64bit.

  • Simulator: NS 2.35, Language : TCL and AWK script, (C++)

+ Software Tools & Technologies
  • OS : Window 7 (Cygwin) / Ubuntu 12.04 LTS 64bit.

  • Simulator: NS 2.35, Language : TCL and AWK script, (C++)

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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