# Robust Security Solution to Countermeasure of Malicious Nodes for the Security of MANET

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3 In wormhole attack, the attacker gets themselves in strong strategic location in the network. They make the use of their location i.e. they have shortest path between the nodes as shown in the Fig. 3.4 above. 4. PROPOSED APPROACH Quantitative Approach This approach is used when the researchers wants verify the theories they proposed, or observe the information in greater detail Qualitative Approach This approach follows the strategies such as ethnographies, phenomenology and grounded theories. When the researchers want to study the context or focusing on single phenomenon or concepts then they used qualitative approach to achieve their desired goals. 4.2 Our Proposed Method In our proposed work we have used both quantitative and qualitative approaches. This approach starts by studying the elated literature specific to security issues in MANETs and Manet s literature review is followed by simulation modeling. The results are gathered and analyzed and conclusions are drawn on the basis of the results obtained from simulation. The proposed work contributes the analysis in the graphical form to give a clear comparison between various parameters and techniques. 4.3 Problem Identification and Selection The most important phase is when, it is important to select the proper problem area. Different areas are studied with in mind about the interest of the problem faced and challenges in the MANET. Most of the time is given to this phase to select the MANET s issue. The proposed work selected MANET as the area of interest and within MANET the focus was given to the security issues and to counter measure the same. 4.4 Proposed Algorithm Algorithm Hop count=0; Path length =0; Reachability =0; For attack node (percentage) =0:1:100 For source = 1to N-1 For destination= source + 1 to N For iteration 1 to 30 Distribute node randomly If (path exist=y) Calculate Path length=total distance from S to D ; Hop count= number of intermediate nodes; Reachability =reachability+1; PDR=total packets/total nodes; Efficiency=delivered packets/available packets; Simulation time= total distance/speed; Average reachaability=(2*reachability/n(n-1)*25); AVERAGE PATH length= path length/reachability; Average hope count=hop count/ reachability; 5. SIMULATION RESULTS We have proposed the method to improve the system s efficiency using different routing protocols (AODV, DSDV etc). We have also proposed a method to countermeasure these attacks using cryptography security keys. Figure 5.1: Black hole effects on system efficiency Figure 5.2: worm hole effects on syst em efficiency Figure5.3: Effect of Attacks on PDR of the network

4 5.1 ROUTING PROTOCOL APPRAOCHES (AODV, DSDV) Figure 5.8: Comparing of Secured Routing Protocols Figure 5.4: throughput of the system with protocols 5.2 OVERALL COMPARISON Figure 5.5 Comparing AODV & DSDV Figure 5.6: Improved AODV Figure 5.7 Improved DSDV Figure 5.9: Overall comparison of the system efficiency CONCLUSION In our proposed work, we have analyzed the behavior and challenges of security threats in mobile Ad-Hoc networks with solution finding technique using improved routing protocols. In our study we analyzed that Black Hole attack & worm Hole attack with different scenarios with respect to the performance parameters of end-to-end delay, throughput and network load etc. In a network it is important for a protocol to be redundant and efficient in term of security. We have analyzed the vulnerability of two protocols AODV and DSDV have more severe effect when there is higher number of nodes and more route requests. Finally we have compared the performance of the different attacks with different routing protocols under different parameters. FUTURE SCOPE There is a need to analyze Black Hole attack in other MANETs routing protocols such as TORA and GRP. Other types of attacks such as Jellyfish and Sybil attacks are needed to be studied in comparison with Black Hole attack. They can be categorized on the basis of how much they affect the performance of the network. Black Hole attack can also attack the other way around i.e. as Sleep Deprivation attack. The detection of this behavior of Black Hole attack as well as the elimination strategy for such behavior has to be carried out for further research. Further the work can be extended considering more secure environment using different security methods

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