A Dual Attack Detection Technique to Identify Black and Gray Hole Attacks Using an Intrusion Detection System and a Connected Dominating Set in MANETs

被引:34
|
作者
Zardari, Zulfigar Ali [1 ,2 ]
He, Jingsha [1 ,2 ]
Zhu, Nafei [1 ,2 ]
Mohammadani, Khalid Hussain [3 ]
Pathan, Muhammad Salman [1 ,2 ]
Hussain, Muhammad Iftikhar [1 ,2 ]
Memon, Muhammad Qasim [4 ]
机构
[1] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
[2] Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Beijing 100124, Peoples R China
[3] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
[4] Beijing Normal Univ, Advance Innovat Ctr Future Educ, Beijing 100875, Peoples R China
来源
FUTURE INTERNET | 2019年 / 11卷 / 03期
基金
中国国家自然科学基金;
关键词
MANET; DoS attack; black hole; gray hole; IDS node; CDS; status packet; dual attack; AD HOC NETWORKS; PROTOCOL; PERFORMANCE; SECURITY; NODES;
D O I
10.3390/fi11030061
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A mobile ad-hoc network (MANET) is a temporary network of wireless mobile nodes. In a MANET, it is assumed that all of the nodes cooperate with each other to transfer data packets in a multi-hop fashion. However, some malicious nodes don't cooperate with other nodes and disturb the network through false routing information. In this paper, we propose a prominent technique, called dual attack detection for black and gray hole attacks (DDBG), for MANETs. The proposed DDBG technique selects the intrusion detection system (IDS) node using the connected dominating set (CDS) technique with two additional features; the energy and its nonexistence in the blacklist are also checked before putting the nodes into the IDS set. The CDS is an effective, distinguished, and localized approach for detecting nearly-connected dominating sets of nodes in a small range in mobile ad hoc networks. The selected IDS nodes broadcast a kind of status packet within a size of the dominating set for retrieving the complete behavioral information from their nodes. Later, IDS nodes use our DDBG technique to analyze the collected behavioral information to detect the malicious nodes and add them to the blacklist if the behavior of the node is suspicious. Our experimental results show that the quality of the service parameters of the proposed technique outperforms the existing routing schemes.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Intrusion Detection for Black Hole and Gray Hole in MANETs
    She, Chundong
    Yi, Ping
    Wang, Junfeng
    Yang, Hongshen
    [J]. KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2013, 7 (07): : 1721 - 1736
  • [2] SAODV: Black Hole and Gray Hole Attack Detection Protocol in MANETs
    Dhende, Sandeep
    Musale, Sandeep
    Shirbahadurkar, Suresh
    Najan, Anand
    [J]. 2017 2ND IEEE INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET), 2017, : 2391 - 2394
  • [3] Gray Hole Attack Detection in MANETs
    Patil, Sarika U.
    [J]. 2017 2ND INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2017, : 20 - 26
  • [4] Dynamic Cluster Head Selection to Detect Gray Hole Attack using Intrusion Detection System in MANETs
    Funde, Rahul
    Chandre, Pankaj
    [J]. 6TH INTERNATIONAL CONFERENCE ON COMPUTER & COMMUNICATION TECHNOLOGY (ICCCT-2015), 2015, : 73 - 77
  • [5] Cross centric intrusion detection system for secure routing over black hole attacks in MANETs
    Rajendran, N.
    Jawahar, P. K.
    Priyadarshini, R.
    [J]. COMPUTER COMMUNICATIONS, 2019, 148 : 129 - 135
  • [6] Detection and Removal of Gray, Black and Cooperative Black Hole Attacks in AODV Technique
    Ibrahim, Hosny M.
    Omar, Nagwa M.
    William, Ebram K.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2015, 6 (05) : 60 - 70
  • [7] Cluster-based Technique for Detection and Prevention of Black-Hole Attack in MANETS
    Saurabh, Vidya Kumari
    Sharma, Roopesh
    Itare, Ravikant
    [J]. 2017 INTERNATIONAL CONFERENCE OF ELECTRONICS, COMMUNICATION AND AEROSPACE TECHNOLOGY (ICECA), VOL 2, 2017, : 489 - 494
  • [8] Gray and Black Hole Attack Identification using Control Packets in MANETs
    Dhaka, Arvind
    Nandal, Amita
    Dhaka, Raghuveer S.
    [J]. ELEVENTH INTERNATIONAL CONFERENCE ON COMMUNICATION NETWORKS, ICCN 2015/INDIA ELEVENTH INTERNATIONAL CONFERENCE ON DATA MINING AND WAREHOUSING, ICDMW 2015/NDIA ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE AND SIGNAL PROCESSING, ICISP 2015, 2015, 54 : 83 - 91
  • [9] Hybrid Detection of Black hole and Gray hole attacks in MANET
    Rathiga, P.
    Sathappan, S.
    [J]. 2016 INTERNATIONAL CONFERENCE ON COMPUTATION SYSTEM AND INFORMATION TECHNOLOGY FOR SUSTAINABLE SOLUTIONS (CSITSS), 2016, : 135 - 140
  • [10] Black Hole attack Detection using Fuzzy based Intrusion Detection Systems in MANET
    Moudni, Houda
    Er-rouidi, Mohamed
    Mouncif, Hicham
    El Hadadi, Benachir
    [J]. 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