• DocumentCode
    256279
  • Title

    Performance improvement of deep packet inspection for Intrusion Detection

  • Author

    Parvat, T.J. ; Chandra, P.

  • Author_Institution
    G.G.S. Indratrastha Univ. Dwarka, New Delhi, India
  • fYear
    2014
  • fDate
    22-24 Dec. 2014
  • Firstpage
    224
  • Lastpage
    228
  • Abstract
    The development in anomaly and misuse detection in this decade is crucial as web services grow vast. Managing secure network is a challenge today. The objectives vary according to the infrastructure management and security policy. There are various ways to check stateful packet inspection and Deep Packet inspection (DPI). Identify payload traffic using DPI, Network security, Privacy and QoS. The functions of DPI are protocol detection, anti-virus, anti-malware and Intrusion Detection System (IDS). The detection engine may support by a signatures or heuristics. Most of the algorithms do training and testing, it takes approximately double time. The paper suggests a new model to improve performance of Intrusion detection system by using in/out based attributes of records. It takes a comparative less time and good accuracy than the existing classifiers.
  • Keywords
    computer network management; computer network performance evaluation; computer network security; computer viruses; data privacy; program testing; protocols; quality of service; DPI; IDS; QoS; Web services; anomaly detection; anti-malware; anti-virus; deep packet inspection; heuristics; in/out based attributes; infrastructure management; intrusion detection system; misuse detection; network privacy; network security; payload traffic; protocol detection; secure network management; security policy; Accuracy; Computational modeling; Hidden Markov models; Inspection; Intrusion detection; Training; Accuracy; Deep Packet Inspection; Intrusion Detection; Performance; Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Computing and Networking (GCWCN), 2014 IEEE Global Conference on
  • Conference_Location
    Lonavala
  • Type

    conf

  • DOI
    10.1109/GCWCN.2014.7030883
  • Filename
    7030883