[IJET-V2I3_1P1]

International Journal of Engineering and Techniques - Volume 2 Issue 3, May - June 2016

A Novel Approach to prevent launching of Attacks in MANETs Using CBDS Raghavendra S1, Nagalakshmi S2

Abstract

1(Student ,Dept. ISE, Dr. Ambedkar Institute of Technology, Bangalore, India ) 2(Associate Professor, Dept. ISE, Dr. Ambedkar Institute of Technology, Bangalore, India)

A MANET is a continuously self-configuring, infrastructure-less type network, which consists of number of mobile nodes with wireless network interfaces. In order to make communication among nodes, the nodes demoniacally establish paths among neighbouring nodes. Security in mobile adhoc network is a big challenge because many nodes perform many kinds of misbehaviour.

In this paper, the main focus is on collaborative attacks in MANET using CBDS approach. CBDS is a approach which consolidate asset of proactive and reactive defense method in reverse tracing. In reverse tracing method we compare performance of CBDS approach with DSR and AOMDV routing protocols.

Keywords - Cooperative bait detection scheme (CBDS), Dynamic Source Routing (DSR), Ad-hoc on-demand Multipath Distance Vector (AOMDV), Black Hole I Introduction A MANET is a system of wireless mobile that category of a self configuring network and rapidly developed network which is composed of several movable nodes. Since there is no fixed set of infrastructure and centralized administration, Nodes in MANETs can join and leave the network dynamically. Communication can be done through Wi-Fi connection or alternative medium such as a cellular or satellite communication, all of the transmission links are established through wireless medium.

Transmission takes place in open medium makes the MANETs more vulnerable to security attacks. The mobile hosts dynamically establish paths among one another in order to communicate. Therefore, the success of MANET communication highly relies on the collaboration of the involved mobile nodes. Such dynamism of MANET-based architectures leads to wide variety of attacks.

The presence and collaboration [1]of hostile nodes in the network may corrupt the routing process, causes the malfunctioning of the network operations. The lack of infrastructure in MANETs make the network highly vulnerable to routing attacks such as black hole and gray hole. MANET is widely used in military purpose, disaster area, personal area network and so on. Some MANETs are

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constrained to a limited area of wireless devices while others may be associated to the Internet.

In this paper, we focus on detecting collaborative Black hole attacks and also comparing the performance with DSR and AOMDV routing technique in reverse tracing path.

II Related work: Many schemes have been proposed for detecting malicious node in network, but most of them deals with detecting of single malicious node or requires more assets in terms of cost and time for detecting blackhole attack.

A. Belmehdi et al. [2] proposed MD5 (Message Digest 5) technique, which resolves the issues like launching of gray hole or collaborative blackhole attck. In these situation, preventing and detecting malicious nodes and evade from launching gray hole or collaborative blackhole attacks is a main threat in mobile adhoc network. In this approach it will try to achieve packet delivery ratio and routing overhead will be considered and choosen as performance metrics Xue et al.[3] proposed a mechanism called best-effort faulttolerant routing (BFTR). Their BFTR arrangement uses endto-end salutations to monitor the quality of the routing path,

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International Journal of Engineering and Techniques - Volume 2 Issue 3, May - June 2016 that measures in terms of packet delivery ratio and end to end delay to be chosen by the destination node. If the behaviour of the path deviates from a predefined behavior set for conclusive “good� routes, the source node uses a new route.

The drawbacks of BFTR is that mischievous nodes may still present in the new chosen route, and this scheme is prone to repetitive route discovery processes, which may lead to momentous routing overhead.

In [4], Liu et al. proposed a mechanism which uses concept called 2ACK scheme, which is used for detection of routing immorality in MANETs. In this scheme, two-hop acknowledgement packets are sent in the opposite direction of the routing path to indicate that the data packets have been successfully received. A acknowledgment ratio(Rack) parameter is also used to control the ratio of the received data packets for which the acknowledgment is required. Here proactive schemes is implemented and hence, produces additional routing overhead regardless of the existence of malicious nodes.

due to malicious node and provide better packet delivery ratio.

CBDS comprises three phases: 1. Initial Bait Step 2. Initial Reverse Tracing Phase 3. Shifted To Reactive Defence Phase (Reactive Phase) 1)Initial Bait Step: The objective of the bait phase is to tempt a malicious node to send an answer RREP by sending the bait RREQ, that it has used to advertise itself at this very moment most shortest way to the node that confines the packets that were changed over. To accomplish this objective, the accompanying system is intended to create the destination location of the bait RREQ'. The source node automatically chooses a nearby node. The source node automatically chooses a nearby node.

III Proposed work Cooperative bait detection scheme(CBDS) is a detecting technique which aims for detecting and preventing malicious nodes launching collaborative blackhole attacks in MANETs. In this approach the source node stochastically selects an neighbouring node with which to cooperate, in the sense that the address of this node is used as bait destination address to bait malicious nodes to send a reply RREP message. There by malicious nodes are detected and prevent from participating in the routing operation, using reverse tracing technique. An alarm is sent by destination to the source node to trigger the detection mechanism ,when there is significant drop occurs in the packet delivery ratio.

The CBDS combines the proactive and reactive defence architectures and randomly cooperates with a stochastic adjacent node. It takes help by using the address of the neighbour node as the hook destination address, and it hooks malicious nodes to reply RREP and detects the malicious nodes by the proposed reverse tracing programme. At last, the detected malicious node is listed in the black hole list and notices all nodes in network to stop any communication with them. As a result, it can reduce packet loss that is happened

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Fig. 1 Random Selection of Cooperative Bait

On the off chance that REP intentionally gave no answer RREP, it would be straightforwardly recorded on the blackhole list by the source hub. If the REP node had sent an answer RREP, it would imply that there was no different malicious node in the system, aside from the course that rhad gave; for this situation, the course revelation period of DSR will be begun. The course that REP gives won't be recorded in the decisions gave to the route discovery phase.

2) Reverse Tracing Step: The converse following step is utilized to identify the behaviors of malicious nodes through the route answer to the RREQ' message. On the off chance that a noxious node has gotten the RREQ', it will answer with a false RREP. Likewise, the reverse tracing operation will be directed for node accepting the RREP, with the objective to deduce the dubious information and the incidentally trusted zone in the route.

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International Journal of Engineering and Techniques - Volume 2 Issue 3, May - June 2016 3)Reactive Defence Step: In reactive phase, we use two routing approach. In first approach we use the DSR route discovery ry process is activated and in second approach AOMDV route discovery process is activated. When the route is established and if at the destination, it is found that the packet delivery ratio significantly falls to the threshold, the detection scheme would be triggered again to detect for continuous maintenance and real-time time reaction efficiency .

3) Average End-to-End End Delay: This is deďŹ ned de as the average time taken for a packet to be transmitted from the source to the destination.

Simulation Parameters Parameters Application Traffic Transmission Rate Radio Range Packet Size Channel Data Rate Pause Time Maximum Speed Number of Nodes Area Malicious Node MAC

Values 12CBR 64packets 716m 512bytes 11Mbps 0s 10m/s 40 1500m*1000m 2% 802.11

Simulation Scenario: 1.Simulation results are calculated for fixed number of node ,fixed percentage of malicious nodes, mobility speed at 10ms and by varying routing algorithm in CBDS approach. Under this scenario we can get to know the performance parameters wrt to DSR and AOMDV algorithms. hms.

2. Simulation results are calculated for fixed number of node ,fixed percentage of malicious nodes ,mobility speed at 30ms and by varying routing algorithm in CBDS approach. Under this scenario we can get to know the performance parameters wrt to DSR R and AOMDV algorithms.

Fig.2 CBDS Flow

Performance Evaluation : We have compared the CBDS approach against DSR and AOMDV routing protocol 1)Packet Delivery Ratio: This is deďŹ ned as the he ratio of the number of packets received at the destination and the number of packets sent by the source.

This section gives the detail analysis of the simulation results. Proposed scheme is evaluated against the AOMDV routing protocol. Different parameters like overhead, delay, packet delivery ratio in the node are considered to evaluate ate the results and we will explain them with the help of graphs. The simulation is conducted for 40 nodes .

2) Routing Overhead: This metric represents the ratio of the amount of routing-related related control packet transmissions to the amount of data transmissions

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International Journal of Engineering and Techniques - Volume 2 Issue 3, May - June 2016

Fig.3 Scenario 1 Packet Delivery of Ratio DSR and AOMDV

Fig.4 Scenario 2 Packet Delivery of Ratio DSR and AOMDV

Figure 3 Denotes Packet Delivery of Ratio of DSR and AOMDV. In Reactive path DSR algorith provided only one alternative path to reach destination, but where as AOMDV provide multiple path to reach destination when mallicious node attack the present routing path. Reverse ttracing get trigger when there is significant drop occurs in packet delivery at the destination side.

Figure 4 Denotes even when the speed of mobility is increased AOMDV performance better than DSR routing algorithm.

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Fig.5 Scenario 1 Routing Overhead of DSR and AOMDV

Fig.6 Scenario 2 Routing Overhead of DSR and AOMDV

Figure 5 and Figure 6 Denotes Routing Overhead of DSR and AOMDV routing algorithm.

The overhead of AOMDV has increased because it has to find multiple path to reach destination when reactive re phase in initiated, but where as in DSR it just provide single alternative path to reach destination which in turn reduce the overhead of the network and as the mobility of node increases the overhead also increase in DSR as well as AOMDV because off link failures and reestablishment of

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International Journal of Engineering and Techniques - Volume 2 Issue 3, May - June 2016 links.

For best Packet Delivery Ration AOMDV performs best when compare to DSR ,but there will be slight increase inc in the Routing Overhead and also End To End Delay due to finding of multiples paths in reactive phase of Cooperative Bait Detection scheme.

References

Fig.7 Scenario 1 Average End to End Delay of DSR and AOMDV

[1] Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A Cooperative Bait Detection Approach Jian-Ming Chang, Po-Chun Chun Tsou, Isaac Woungang, HanHan Chieh Chao, and Chin-Feng Feng Lai, Member, IEE IEEE Systems Journal,Volume:9,Issue:1,Issue Date :March.2015 :Marc [2]A. Baadache and A. Belmehdi, “Avoiding blackhole and cooperative blackhole attacks in wireless ad hoc networks,” Intl. J. Comput. Sci. Inf. Security,, vol. 7, no. 1, 2010.

[3 ]Y. Xue and K. Nahrstedt, “Providing fault-tolerant fault ad hoc routing service ce in adversarial environments,” Wireless Pers.Commun., vol. 29, pp. 367– 388, 2004.

[4]K. Liu, D. Pramod, K. Varshney, and K. Balakrishnan, “An Acknowledgement based approach for the detection of routing misbehavior in MANETs,” IEEE IEE Trans. Mobile Compute., vol. 6, no. 5, pp. 536–550, 550, Ma M

Fig.8 Scenario 2 Average End to End Delay of DSR and AOMDV

Figure 7 and 8 Denotes Average End to End Delay of DSR and AOMDV, end to end delay increased in AOMDV because it has to find out multiple alternative path which in turn delay in the network.

IV Conclusion In this paper, A mechanism called CBDS is used for detecting malicious node in MANETs under collaborative attacks.Simulation results are revealed that CBDS is performed on DSR and AOMDV routing algorithm.

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International Journal of Engineering and Techniques - Volume 2 Issue 3, May - June 2016

ISSN: 2395-1303

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