Biologically inspired artificial intrusion detection system for detecting wormhole attack in MANET

被引:0
|
作者
T. V. P. Sundararajan
S. M. Ramesh
R. Maheswar
K. R. Deepak
机构
[1] Bannari Amman Institute of Technology,
[2] Sri Krishna College of Technology,undefined
来源
Wireless Networks | 2014年 / 20卷
关键词
Routing; Wormhole; Intrusion; Detection; Anomaly;
D O I
暂无
中图分类号
学科分类号
摘要
A mobile ad hoc network (MANET) does not have traffic concentration points such as gateway or access points which perform behaviour monitoring of individual nodes. Therefore, maintaining the network function for the normal nodes when other nodes do not forward and route properly is a big challenge. One of the significant attacks in ad hoc network is wormhole attack. In this wormhole attack, the adversary disrupts ad hoc routing protocols using higher bandwidth and lower-latency links. Wormhole attack is more hidden in character and tougher to detect. So, it is necessary to use mechanisms to avoid attacking nodes which can disclose communication among unauthorized nodes in ad hoc networks. Mechanisms to detect and punish such attacking nodes are the only solution to solve this problem. Those mechanisms are known as intrusion detection systems (IDS). In this paper, the suggested biological based artificial intrusion detection system (BAIDS) include hybrid negative selection algorithm (HNSA) detectors in the local and broad detection subsection to detect anomalies in ad hoc network. In addition to that, response will be issued to take action over the misbehaving nodes. These detectors employed in BAIDS are capable of discriminating well behaving nodes from attacking nodes with a good level of accuracy in a MANET environment. The performance of BAIDS in detecting wormhole attacks in the background of DSR, AODV and DSDV routing protocols is also evaluated using Qualnet v 5.2 network simulator. Detection rate, false alarm rate, packet delivery ratio, routing overhead are used as metrics to compare the performance of HNSA and the BAIDS technique.
引用
收藏
页码:563 / 578
页数:15
相关论文
共 50 条
  • [21] Fuzzy based intrusion detection system in MANET
    Edwin Singh C.
    Celestin Vigila S.M.
    Measurement: Sensors, 2023, 26
  • [22] A Novel Intrusion Detection System Based on Trust Evaluation to Defend Against DDoS Attack in MANET
    Poongodi, M.
    Bose, S.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2015, 40 (12) : 3583 - 3594
  • [23] A Context Adaptive Intrusion Detection System for MANET
    Cheng, Bo-Chao
    Tseng, Ryh-Yuh
    COMPUTER COMMUNICATIONS, 2011, 34 (03) : 310 - 318
  • [24] A Multicast Effective Intrusion Detection System for MANET
    Jayasankar, T.
    Shanthi, S.
    Bhavadharini, R. M.
    Thiruvengadam, C.
    BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS, 2020, 13 (02): : 132 - 136
  • [25] CMIDS: Collaborative MANET Intrusion Detection System
    Carvalho, Jeronymo M. A.
    Costa, Paulo C. G.
    2016 IEEE INTERNATIONAL CONFERENCE ON CYBER CONFLICT (CYCON U.S.), 2016, : 29 - 33
  • [26] Black Hole attack Detection using Fuzzy based Intrusion Detection Systems in MANET
    Moudni, Houda
    Er-rouidi, Mohamed
    Mouncif, Hicham
    El Hadadi, Benachir
    10TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2019) / THE 2ND INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40 2019) / AFFILIATED WORKSHOPS, 2019, 151 : 1176 - 1181
  • [27] A Novel Cross Layer Intrusion Detection System in MANET
    Shrestha, Rakesh
    Han, Kyong-Heon
    Choi, Dong-You
    Han, Seung-Jo
    2010 24TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA), 2010, : 647 - 654
  • [28] Watchdog and Pathrater based Intrusion Detection System for MANET
    Saifuddin, Khaled Mohammed
    Bin Ali, Abu Jobayer
    Ahmed, Abu Shakil
    Alam, Sk. Shariful
    Ahmad, Abu Saleh
    2018 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATION & COMMUNICATION TECHNOLOGY (ICEEICT), 2018, : 168 - 173
  • [29] An Enhanced Intrusion Detection System for Routing Attacks in MANET
    Abirami, K. Rama
    Sumithra, M. G.
    Rajasekaran, J.
    PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING & COMMUNICATION SYSTEMS (ICACCS), 2013,
  • [30] Machine Learning Methods for Intrusive Detection of Wormhole Attack in Mobile Ad Hoc Network (MANET)
    Abdan, Masoud
    Seno, Seyed Amin Hosseini
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022