Intrusion Detection Systems of ICMPv6-based DDoS attacks

被引:14
|
作者
Elejla, Omar E. [1 ]
Belaton, Bahari [1 ]
Anbar, Mohammed [2 ]
Alnajjar, Ahmad [2 ]
机构
[1] Univ Sains Malaysia, Sch Comp Sci, Gelugor, Penang, Malaysia
[2] Univ Sains Malaysia, Natl Adv Ctr NAv6 IPv6, Gelugor, Penang, Malaysia
来源
NEURAL COMPUTING & APPLICATIONS | 2018年 / 30卷 / 01期
关键词
Intrusion Detection System; IDS; ICMPv6; IPv6; networks; DoS; DDoS; ANOMALY DETECTION;
D O I
10.1007/s00521-016-2812-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks are thorny and a grave problem of today's Internet, resulting in economic damages for organizations and individuals. DoS and DDoS attacks that are using Internet Control Message Protocol version six (ICMPv6) messages are the most common attacks against the Internet Protocol version six (IPv6). They are common because of the necessary inclusion of the ICMPv6 protocol in any IPv6 network to work properly. Intrusion Detection Systems (IDSs) of the Internet Protocol version four (IPv4) can run in an IPv6 environment, but they are unable to solve its security problems such as ICMPv6-based DDoS attacks due to the new characteristics of IPv6, such as Neighbour Discovery Protocol and auto-configuration addresses. Therefore, a number of IDSs have been either exclusively proposed to detect IPv6 attacks or extended from existing IPv4 IDSs to support IPv6. This paper reviews and classifies the detection mechanisms of the existing IDSs which are either proposed or extended to tackle ICMPv6-based DDoS attacks. To the best of the authors' knowledge, it is the first review paper that explains and clarifies the problems of ICMPv6-based DDoS attacks and that classifies and criticizes the existing detection.
引用
收藏
页码:45 / 56
页数:12
相关论文
共 50 条
  • [1] Intrusion Detection Systems of ICMPv6-based DDoS attacks
    Omar E. Elejla
    Bahari Belaton
    Mohammed Anbar
    Ahmad Alnajjar
    [J]. Neural Computing and Applications, 2018, 30 : 45 - 56
  • [2] Comparison of Classification Algorithms on ICMPv6-Based DDoS Attacks Detection
    Elejla, Omar E.
    Belaton, Bahari
    Anbar, Mohammed
    Alabsi, Basim
    Al-Ani, Ahmed K.
    [J]. COMPUTATIONAL SCIENCE AND TECHNOLOGY, 2019, 481 : 347 - 357
  • [3] Flow-Based IDS for ICMPv6-Based DDoS Attacks Detection
    Elejla, Omar E.
    Anbar, Mohammed
    Belaton, Bahari
    Alijla, Basem O.
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2018, 43 (12) : 7757 - 7775
  • [4] Flow-Based IDS for ICMPv6-Based DDoS Attacks Detection
    Omar E. Elejla
    Mohammed Anbar
    Bahari Belaton
    Basem O. Alijla
    [J]. Arabian Journal for Science and Engineering, 2018, 43 : 7757 - 7775
  • [5] ICMPv6-Based DoS and DDoS Attacks and Defense Mechanisms: Review
    Elejla, Omar E.
    Anbar, Mohammed
    Belaton, Bahari
    [J]. IETE TECHNICAL REVIEW, 2017, 34 (04) : 390 - 407
  • [6] Labeled flow-based dataset of ICMPv6-based DDoS attacks
    Elejla, Omar E.
    Anbar, Mohammed
    Belaton, Bahari
    Hamouda, Shady
    [J]. NEURAL COMPUTING & APPLICATIONS, 2019, 31 (08): : 3629 - 3646
  • [7] Labeled flow-based dataset of ICMPv6-based DDoS attacks
    Omar E. Elejla
    Mohammed Anbar
    Bahari Belaton
    Shady Hamouda
    [J]. Neural Computing and Applications, 2019, 31 : 3629 - 3646
  • [8] ICMPv6-Based DoS and DDoS Attacks Detection Using Machine Learning Techniques, Open Challenges, and Blockchain Applicability: A Review
    Tayyab, Mohammad
    Belaton, Bahari
    Anbar, Mohammed
    [J]. IEEE ACCESS, 2020, 8 : 170529 - 170547
  • [9] Brief of Intrusion Detection Systems in Detecting ICMPv6 Attacks
    Bdair, Adnan Hasan
    Abdullah, Rosni
    Manickam, Selvakumar
    Al-Ani, Ahmed K.
    [J]. COMPUTATIONAL SCIENCE AND TECHNOLOGY (ICCST 2019), 2020, 603 : 199 - 213
  • [10] ICMPv6-based DDoS Flooding-Attack Detection Using Machine and Deep Learning Techniques
    El Ksimi, Ali
    Leghris, Cherkaoui
    Lafraxo, Samira
    Verma, Vinod Kumar
    [J]. IETE JOURNAL OF RESEARCH, 2023, 70 (04) : 3753 - 3762