06-09-2016, 12:21 PM
Defending Against Collaborative Attacks by
Malicious Nodes in MANETs: A Cooperative Bait
Detection Approach
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DUE to the widespread availability of mobile devices, mobile ad hoc networks (MANETs) [1], [2] have been widely used for various important applications such as military crisis operations and emergency preparedness and response operations. The lack of any infrastructure added with the dynamic topology
feature of MANETs make these networks highly vulnerable to routing attacks such as black hole and gray hole (known as variants of blackhole attacks). In blackhole attacks (see Fig. 1), a node transmits a malicious broadcast informing that it has the shortest path to the destination, with the goal of intercepting messages. Many research works have investigated the problem of malicious node detection in MANETs. This paper proposes a detection scheme called the cooperative bait detection scheme (CBDS), which aims at detecting and preventing malicious nodes launching grayhole/collaborative black hole attacks in MANETs. The goal of the bait phase is to entice a malicious node to send a reply RREP by sending the bait RREQ_ that it has used to advertise itself as having the shortest path to the node that detains the packets that were coverted. The reverse tracing program is used to detect the behaviors of malicious nodes through the route reply to the RREQ_ message.
Performance Evaluation: -
A. Simulation Parameters
B. Performance Metrics:
1) Packet Delivery Ratio
2) Routing Overhead
3) End-to-End Delay
4) Throughput
Two simulation scenarios are considered:
1) Scenario 1: Varying the percentage of malicious nodes
with a fixed mobility.
2) Scenario 2: Varying the mobility of nodes under fixed
percentage of malicious nodes.
• we study the packet delivery ratio of the CBDS andDSR for different thresholds when the percentage of malicious nodes in the network varies from 0% to 40%.
• we study the routing overhead of the CBDS and DSR for different thresholds.
• we study the end-to-end delay of the CBDS and DSR for different thresholds.
• we study the throughput of the CBDS and DSR for different thresholds.
• we compare DSR, 2ACK, BFTR, and CBDS in terms of packet delivery ratio and routing overhead when the malicious nodes increase in the network. In this scenario, the maximum speed of nodes is varied from
0 to 20 m/s, and the percentage of malicious nodes is fixed to 20%.
• we study the packet delivery ratio of the CBDS and DSR for different thresholds. The threshold value is set to 85%,95%, and the dynamic threshold, respectively.
• we study the routing overhead of the CBDS and DSR for different thresholds. The threshold value is set to 85%,95%, and the dynamic threshold, respectively.
• we study the throughput of the CBDS and DSR for different thresholds. The threshold value is set to 85%, 95%, and the dynamic threshold, respectively.
• we study the end-to-end delay of the CBDS and DSR for different thresholds. The threshold value is set to 85%,95%, and the dynamic threshold, respectively.
• we have proposed a new mechanism (called the CBDS) for detecting malicious nodes in MANETs under gray/collaborative black hole attacks. Our simulation results revealed that the CBDS outperforms the DSR, 2ACK, and BFTR
schemes, chosen as benchmark schemes, in terms of routing
overhead and packet delivery ratio.
1) investigate the feasibility of adjusting our CBDS approach to address other types of collaborative attacks on MANETs.
2) investigate the integration of the CBDS with other
well-known message security schemes in order to construct a
comprehensive secure routing framework to protect MANETs
against miscreants.