Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks

Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks

Bibliographic Details
Main Author: Prathapani, Anoosha
Language:English
Published: University of Cincinnati / OhioLINK 2010
Subjects:
Electrical Engineering
AODV
BLACKHOLE
HONEYPOTS
MALICIOUS
SPOOFED
WIRELESS MESH NETWORKS
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=ucin1289939348
id ndltd-OhioLink-oai-etd.ohiolink.edu-ucin1289939348
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-ucin12899393482021-08-03T06:14:20Z Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks Prathapani, Anoosha Electrical Engineering AODV BLACKHOLE HONEYPOTS MALICIOUS SPOOFED WIRELESS MESH NETWORKS <p>A Wireless Mesh Network (WMN) is a promising means to provide low-cost broadband Internet access. The routing protocols naively assume all nodes in the network to be non-malicious. The open architecture of WMN, multi-hop nature of communication, different management styles, and wireless communication paves way for malicious attackers. The attackers can exploit hidden loopholes in the multipath mesh routing protocol to conduct a suction attack called a “blackhole attack”. The attacker can falsify routing metric such as hop count, shorten transmission time to reach any destination and thereby suck the network traffic.</p><p>We propose a novel strategy by employing mobile honeypot agents that utilize their topological knowledge and detect such spurious route advertisements. They are deployed as roaming software agents that tour the network and lure attackers by sending Route Request (RREQ) advertisements. We first examine the threat of an active Blackhole attack, and then, using our intelligent Honeypot mechanism, we try to control it. We collect valuable information on attacker’s strategy from the intrusion logs gathered at the honeypot. We finally evaluate the effectiveness of proposed architecture using simulation in ns-2 for random topology and grid topology. The performance of the proposed detection approach has shown the encouraging results. The performance of the proposed detection scheme is shown to be increased by 80% for grid topology and 77% for random topology.</p> 2010 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1289939348 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1289939348 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center.
collection NDLTD
language English
sources NDLTD
topic Electrical Engineering
AODV
BLACKHOLE
HONEYPOTS
MALICIOUS
SPOOFED
WIRELESS MESH NETWORKS
spellingShingle Electrical Engineering
AODV
BLACKHOLE
HONEYPOTS
MALICIOUS
SPOOFED
WIRELESS MESH NETWORKS
Prathapani, Anoosha
Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks
author Prathapani, Anoosha
author_facet Prathapani, Anoosha
author_sort Prathapani, Anoosha
title Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks
title_short Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks
title_full Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks
title_fullStr Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks
title_full_unstemmed Intelligent Honeypot Agents for Detection of Blackhole Attack in Wireless Mesh Networks
title_sort intelligent honeypot agents for detection of blackhole attack in wireless mesh networks
publisher University of Cincinnati / OhioLINK
publishDate 2010
url http://rave.ohiolink.edu/etdc/view?acc_num=ucin1289939348
work_keys_str_mv AT prathapanianoosha intelligenthoneypotagentsfordetectionofblackholeattackinwirelessmeshnetworks
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