Radha Raman Chandan and P.K.Mishra
Department of Computer Science & DST-CIMS,
Institute of Science, Banaras Hindu University, Varanasi
Radha Raman Chandan and P.K.Mishra
Department of Computer Science & DST-CIMS, Institute of Science, Banaras Hindu University, Varanasi
Department of Computer Science & DST-CIMS, Institute of Science, Banaras Hindu University, Varanasi
Abstract
The Mobile Adhoc Network (MANET) is a wireless network model for infrastructure-less
communication, and it provides numerous applications in different areas. The MANET is vulnerable to a
Black-hole attack, and it affects routing functionality by dropping all the incoming packets purposefully.
The Black-hole attackers pretend that it always has the best path to the destination node to mislead the
source nodes. Trust is the critical factor for detecting and isolating the Black-hole attackers from the
network. However, the harsh channel conditions make it difficult to differentiate the Black-hole routing
activities and accurate trust measurement. Hence, incorporating the consensus-based trust evidence
collection from the neighbouring nodes improves the accuracy of trust. For improving the accuracy of
trust, this work suggests Consensus Routing and Environmental DIscrete Trust (CREDIT) Based Secure
AODV. The CREDIT incorporates Discrete and Consensus trust information. The Discrete parameters
represent the specific characteristics of the Black-hole attacks, such as routing behaviour, hop count
deviation, and sequence number deviation. The direct trust accurately differentiates the Black-hole
attackers using Discrete parameters, only when the nodes perform sufficient communication between
the nodes. To solve such issues, the CREDIT includes the Consensus-based trust information. However,
secure routing against the Black-hole attack is challenging due to incomplete preferences. The in-degree
centrality and Importance degree measurement on the collected consensus-based trust from decisionmakers solve the incomplete preference issue as well as improves the accuracy of trust. The performance
of the proposed scheme is evaluated using Network Simulator-2 (NS2). From the simulation results, it
is proved that the detection accuracy and throughput of the proposed CREDIT are substantially high
and the proposed CREDIT scheme outperforms the existing work
The Mobile Adhoc Network (MANET) is a wireless network model for infrastructure-less
communication, and it provides numerous applications in different areas. The MANET is vulnerable to a
Black-hole attack, and it affects routing functionality by dropping all the incoming packets purposefully.
The Black-hole attackers pretend that it always has the best path to the destination node to mislead the
source nodes. Trust is the critical factor for detecting and isolating the Black-hole attackers from the
network. However, the harsh channel conditions make it difficult to differentiate the Black-hole routing
activities and accurate trust measurement. Hence, incorporating the consensus-based trust evidence
collection from the neighbouring nodes improves the accuracy of trust. For improving the accuracy of
trust, this work suggests Consensus Routing and Environmental DIscrete Trust (CREDIT) Based Secure
AODV. The CREDIT incorporates Discrete and Consensus trust information. The Discrete parameters
represent the specific characteristics of the Black-hole attacks, such as routing behaviour, hop count
deviation, and sequence number deviation. The direct trust accurately differentiates the Black-hole
attackers using Discrete parameters, only when the nodes perform sufficient communication between
the nodes. To solve such issues, the CREDIT includes the Consensus-based trust information. However,
secure routing against the Black-hole attack is challenging due to incomplete preferences. The in-degree
centrality and Importance degree measurement on the collected consensus-based trust from decisionmakers solve the incomplete preference issue as well as improves the accuracy of trust. The performance
of the proposed scheme is evaluated using Network Simulator-2 (NS2). From the simulation results, it
is proved that the detection accuracy and throughput of the proposed CREDIT are substantially high
and the proposed CREDIT scheme outperforms the existing work
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