TY - GEN
T1 - A distributed and cooperative black hole node detection and elimination mechanism for ad hoc networks
AU - Yu, Chang Wu
AU - Wu, Tung Kuang
AU - Cheng, Rei Heng
AU - Chang, Shun Chao
PY - 2007/12/1
Y1 - 2007/12/1
N2 - A mobile node in ad hoc networks may move arbitrarily and acts as a router and a host simultaneously. Such a characteristic makes nodes in MANET vulnerable to potential attacks. The black hole problem, in which some malicious nodes pretend to be intermediate nodes of a route to some given destinations and drop any packet that subsequently goes through it, is one of the major types of attack. In this paper, we propose a distributed and cooperative mechanism to tackle the black hole problem. The mechanism is distributed so that it can fit with the ad hoc nature of network, and nodes in the protocol work cooperatively together so that they can analyze, detect, and eliminate possible multiple black hole nodes in a more reliable fashion. Simulation results show that our method achieves a high black hole detection rate and good packet delivery ratio, while the overhead is comparatively lower as the network traffic increases.
AB - A mobile node in ad hoc networks may move arbitrarily and acts as a router and a host simultaneously. Such a characteristic makes nodes in MANET vulnerable to potential attacks. The black hole problem, in which some malicious nodes pretend to be intermediate nodes of a route to some given destinations and drop any packet that subsequently goes through it, is one of the major types of attack. In this paper, we propose a distributed and cooperative mechanism to tackle the black hole problem. The mechanism is distributed so that it can fit with the ad hoc nature of network, and nodes in the protocol work cooperatively together so that they can analyze, detect, and eliminate possible multiple black hole nodes in a more reliable fashion. Simulation results show that our method achieves a high black hole detection rate and good packet delivery ratio, while the overhead is comparatively lower as the network traffic increases.
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M3 - Conference contribution
AN - SCOPUS:38549083086
SN - 354077016X
SN - 9783540770169
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 538
EP - 549
BT - Emerging Technologies in Knowledge Discovery and Data Mining - PAKDD 2007 International Workshops, Revised Selected Papers
T2 - Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007
Y2 - 22 May 2007 through 22 May 2007
ER -