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An Intelligent Defense and Filtration Platform for Network Traffic

  • Mehrnoosh MonshizadehEmail author
  • Vikramajeet Khatri
  • Buse Atli
  • Raimo Kantola
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10866)

Abstract

Hybrid Anomaly Detection Model (HADM) is a security platform to detect and prevent cyber-attacks on communication networks. The platform uses a combination of linear and learning algorithms combined with protocol analyzer. The linear algorithms filter and extract distinctive attributes and features of the cyber-attacks while the learning algorithms use these attributes and features to identify new types of cyber-attacks. The protocol analyzer in this platform classifies and filters vulnerable protocols to avoid unnecessary computation load. The use of linear algorithms in conjunction with learning algorithms allows the HADM to achieve improved efficiency in terms of accuracy and computation time in order to detect cyber-attacks over existing solutions.

Keywords

Security Cloud computing Internet of things Machine learning Anomaly detection 

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Nokia Bell LabsEspooFinland
  2. 2.Department of ComnetAalto UniversityEspooFinland

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