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Essay: Ad hoc networks

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  • Published: 23 October 2015*
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No predefine range of Network – In Ad-hoc network there is no predefine range of network. Node work in dynamic environment. Node can easily join and leave the wireless medium. Attacks include eaves dropping, Impersonation, tempering, replay and denial of service attack [1].
‘ End to End packet Delay: -Ad-hoc wireless network is based on mobile node..Due to hidden terminals and path break, it increases the error rate and End to End packet delivery ratio in wireless medium.
‘ Lack of Energy Resources: – In Ad-hoc network limited energy resource, No alternate power resource. Node operation is depending on the battery power. When attacker attack on the target node, Congestion in the network increase due to requesting fake connection request causing its battery power lost [13].
‘ Transmission Range: – In wireless networks limited radio band and wired network can offer high data rate in comparison of wireless medium. Thesis requires the routing protocol in wireless networks to use the bandwidth always in an optimal manner by keeping the overhead as long as possible.
‘ Node acts as Router: – In MANETs node rely on their neighbors to route there message to the destination, due to limited transmission range. Hence node in MANETs work as host as well as routers and routing is performed in multiple hope manners.
3.3 Vulnerability of AODV Protocol
From the perspective of attacker’s routing protocol is more vulnerable. The fig.3.1 shows the taxonomy for misusing AODV protocol. In this Vulnerability of AODV is basically divided in packet drop, modify and forward, forge reply, active forge. Active forge is divided in send fake route request and send fake route reply. In this dissertation misuse of the RREP message and packet drop. AODV protocol is attacked in the following ways. The attackers drop the packets and send a fake message for the receiver routing message.
Fig. 3.1 Taxonomy of AODV protocol vulnerability
3.4 Literature Review
3.4.1 PPN: Prime Product Number approach to malicious Node Detection
Prime Product Number approach to solve the malicious node problem [1] by prevention and removal. It proposed a scheme to mitigate the adverse effects of misbehaving node. Key contribution of this approach is , it assume that each node in the network has a specific prime number which belong to node unchanged identity. In this scheme MANET organized in to number of cluster in such a way that at least one cluster is a member of every node which is called cluster head. When destination node and intermediate node generate route reply message to the source node which is the product of prime number from destination node to source node and other information. If reply information is right and prime product number is fully divisible then node is trustworthy node otherwise call the removal process of the node.
The main limitation of this approach is that first give the prime number to every node in MANET, cannot check the behavior of malicious node before assigned the prime number. if malicious node is cluster head how can find out. It is slow process. End to end delay, through put and packet delivery ratio is not improve.
3.4.2 Counter Algorithm approach for securing and preventing AODV routing protocol
In this approach [16] source node without altering intermediate nodes and destination nodes by using a Prior-Receive-Reply method. In this method, checking large difference between the sequence number of source node and destination node or intermediate node who has sent back RREP or not, compare the destination sequence number with source sequence number. If there is more difference between source and destination sequence number then destination node is malicious node.
This method work only source node and destination node. No involvement of intermediate node. It is basis on specific attack black hole. Only sequence number checking technique used.
3.4.3 Effect of malicious node on AODV approach
In this approach [9] it measure the performance of AODV routing protocol in the presence of malicious nodes evaluation has been considered as packet delivery ratio, through put, data packet sent/received and control packet droop. In this no prevention and avoidance technique used for malicious node. It only measures the performance of AODV. No technique is used for improved the performance in through put, end to end delay, packet delivery ratio.
3.4.4 A survey of routing attacks in MANET approach
In this article [13], investigate the security issues in MANET. Author examine attacks such as spoofing and colluding miserly attacks as well as counter measures against such attacks in existing MANET protocol. In this approach gives solution for only specific attack not all. No technique used for handling delivery ratio, end to end delay and throughput.
3.4.5 Flooding attacks prevention in MANET approach
In this approach [20] algorithm is discussed for prevention of flooding attack. Node categorized as strangers and friends based on their relationships with their neighboring nodes. For evaluation of its neighbor node trust level a trust estimator is used. End-to-end delay packet delivery ratio is like a various parameter for trust level functioning
3.4.6 CORE approach
In this CORE mechanism approach [11] it is heighten watchdog for isolating and monitoring. Malicious node based on functional reputation, subjective and indirect various types of information on each entity’s rate of collaboration is used for calculation of reputation. Since there is no inducement for spreading negative information maliciously about other nodes, the collaboration technique itself is prevented denial of service attack.
4.7 Comparison Table
Method Change
in routing protocol Quality
of Service Attack Type Issues
PPN YES Time consuming,
Network throughput increases at the cost of a Higher over head Malicious Node attack ‘ Malicious node is not easily identified with any delay.
‘ More memory overhead occur
Counter Algorithm No Throughput not measure, malicious node vary Black hole attack ‘ Not implements many attacks.
‘ Not Measure the performance of Throughput in this environment
Bounpadith et all No No simulation results Survey paper ‘ Performance during the data transmission
‘ Prevention from other attacks
‘ Detect and remove the malicious node
Neetu Singh Yes End to End delay not measure, time consuming Flood attack ‘ Optimize value of threshold
‘ Improve their performance
Dos and Black Hole attack scheme No Throughput increase and End to End delay decrease DOS and Black Hole attack
Table 3.1 Comparison of previous scheme and Existing Scheme

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