Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach
In mobile ad hoc networks (MANETs), a primary requirement for the establishment of communication among nodes is that nodes should cooperate with each other. In the presence of malevolent nodes, this requirement may lead to serious security concerns; for instance, such nodes may disrupt the routing process. In this context, preventing or detecting malicious nodes launching grayhole or collaborative blackhole attacks is a challenge. This paper attempts to resolve this issue by designing a dynamic source routing (DSR)-based routing mechanism, which is referred to as the cooperative bait detection scheme (CBDS), that integrates the advantages of both proactive and reactive defense architectures. Our CBDS method implements a reverse tracing technique to help in achieving the stated goal. Simulation results are provided, showing that in the presence of malicious-node attacks, the CBDS outperforms the DSR, 2ACK, and best-effort fault-tolerant routing (BFTR) protocols (chosen as benchmarks) in terms of packet delivery ratio and routing overhead (chosen as performance metrics).
DSR involves two main processes: route discovery and route maintenance. To execute the route discovery phase, the source node broadcasts a Route Request (RREQ) packet through the network. If an intermediate node has routing information to the destination in its route cache, it will reply with a RREP to the source node. When the RREQ is forwarded to a node, the node adds its address information into the route record in the RREQ packet. When destination receives the RREQ, it can know each intermediary node’s address among the route.The destination node relies on the collected routing information among the packets in order to send a reply RREP message to the source node along with the whole routing information of the established route.
DISADVANTAGES OF EXISTING SYSTEM:
The lack of any infrastructure added with the dynamic topology feature of MANETs make these networks highly vulnerable ble to routing attacks such as blackhole and grayhole (known as variants of blackhole attacks).
In this regard, the effectiveness of these approaches becomes weak when multiple malicious nodes collude together to initiate a collaborative attack, which may result to more devastating damages to the network.
In this paper, a mechanism [so-called cooperative bait detection scheme (CBDS)] is presented that effectively detects the malicious nodes that attempt to launch grayhole/collaborative blackhole attacks. In our scheme, the address of an adjacent node is used as bait destination address to bait malicious nodes to send a reply RREP message, and malicious nodes are detected using a reverse tracing technique. Any detected malicious node is kept in a blackhole list so that all other nodes that participate to the routing of the message are alerted to stop communicating with any node in that list. Unlike previous works, the merit of CBDS lies in the fact that it integrates the proactive and reactive defense architectures to achieve the aforementioned goal.
ADVANTAGES OF PROPOSED SYSTEM:
In this setting, it is assumed that when a significant drop occurs in the packet delivery ratio, an alarm is sent by the destination node back to the source node to trigger the detection mechanism again.
This function assists in sending the bait address to entice the malicious nodes and to utilize the reverse tracing program of the CBDS to detect the exact addresses of malicious nodes.
Dynamic Source Routing (DSR)
Cooperative Bait Detection
The sensor nodes are randomly distributed in a sensing field. We are using mobile ad hoc network (MANET). This is the infrastructureless network and a node can move independently. In a MANET, each node not only works as a host and also acts as a router. We can find the communication range for all nodes. Every node communicates only within the range. If suppose any node out of the range, node will not communicate those nodes or drop the packets.
Dynamic Source Routing (DSR)
In this project, we are using dynamic source routing algorithm for routing. The DSR involves two main processes: route discovery and route maintenance. The source node broadcast the RREQ through the network. If an intermediate node has the route information to the destination node in its cache, it will reply with a RREP to the source node. When a RREQ is forwarded, the node adds its address information in the RREQ packet. When destination receives the RREQ, it can know all the information about intermediate node. Then the destination will reply with RREP to the source node along with the routing information.
Cooperative Bait Detection Scheme
We propose a detection scheme called Cooperative bait detection scheme (CBDS), which aims to detect the grayhole/collaborative blackhole attacks in MANET. In this scheme, the source node randomly selects the adjacent node is used as a bait destination address to bait malicious node to send a RREP message. We can find the malicious node in the routing operation by using the reverse tracing technique. If there is any malicious node detected in the routing, send the alert message or stop the communication with any node in that list. The CBDS scheme integrates the advantages of proactive detection in the initial stage and the reactive defense architecture to achieve the goal.
In this section, we can evaluate the performance of simulation. We are using the xgraph for evaluate the performance. We choose the three evaluation metrics: Packet delivery ratio – it is the ratio of the number of packet received at destination and number of packet sent by the source, End-to-End delay – the average time taken for a packet to be transmitted from the source to destination, Throughput – number of data received by the destination without any losses.
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 44 Mb.
Monitor : 15 VGA Colour.
Ram : 512 Mb.
Operating system : Windows XP/7/LINUX.
Implementation : NS2
NS2 Version : 2.28
Front End : OTCL (Object Oriented Tool Command Language)
Tool : Cygwin (To simulate in Windows OS)
Jian-Ming Chang, Po-Chun Tsou, Isaac Woungang, Han-Chieh Chao, and Chin-Feng Lai, Member, IEEE, “Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach”, IEEE SYSTEMS JOURNAL, VOL. 9, NO. 1, MARCH 2015