IDEAS home Printed from https://ideas.repec.org/a/igg/jisp00/v12y2018i1p53-62.html
   My bibliography  Save this article

Optimized Packet Filtering Honeypot with Snooping Agents in Intrusion Detection System for WLAN

Author

Listed:
  • Gulshan Kumar

    (Lovely Professional University, Punjab, India)

  • Rahul Saha

    (Lovely Professional University, Punjab, India)

  • Mandeep Singh

    (Lovely Professional University, Punjab, India)

  • Mritunjay Kumar Rai

    (Lovely Professional University, Punjab, India)

Abstract

Wireless LAN networks are considered to be widely used and efficient infrastructure used in different domains of communication. In this paper, we worked on Network Intrusion Detection System (NIDS) to prevent intruder's activities by using snooping agents and honeypot on the network. The idea behind using snooping agents and honeypot is to provide network management in term of monitoring. Honey pot is placed just after the Firewall and intrusion system have strongly coupled synchronize with snooping agents Monitoring is considered at packet level and pattern level of the traffic. Simulation filtered and monitor traffic for highlight the intrusion in the network. Further attack sequence has been created and have shown the effects of attack sequence on scenario which have both honey pot and snoop agent with different network performance parameters like throughput, network load, queuing delay, retransmission attempt and packet. The simulation scenario shows the impact of attack on the network performance.

Suggested Citation

  • Gulshan Kumar & Rahul Saha & Mandeep Singh & Mritunjay Kumar Rai, 2018. "Optimized Packet Filtering Honeypot with Snooping Agents in Intrusion Detection System for WLAN," International Journal of Information Security and Privacy (IJISP), IGI Global, vol. 12(1), pages 53-62, January.
  • Handle: RePEc:igg:jisp00:v:12:y:2018:i:1:p:53-62
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISP.2018010105
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sheikh Tahir Bakhsh & Saleh Alghamdi & Rayan A Alsemmeari & Syed Raheel Hassan, 2019. "An adaptive intrusion detection and prevention system for Internet of Things," International Journal of Distributed Sensor Networks, , vol. 15(11), pages 15501477198, November.
    2. Deng, Yu-Jing & Li, Ya-Qian & Qin, Yu-Hua & Dong, Ming-Ru & Liu, Bin, 2020. "Optimal defense resource allocation for attacks in wireless sensor networks based on risk assessment model," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jisp00:v:12:y:2018:i:1:p:53-62. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.