• Dr.Sumathi Ganesan
• Dr.Manikandan

Mobile ad hoc networks (MANETs) are vulnerable to various types of attacks due to inherently in- secure wireless communication medium and multihop routing communication process. In this paper, we analyze the behavior and impact of JellyFish attack over MANETs. We have implemented and evaluated all three variants of JellyFish attack namely JF-reorder, JF-delay and JF-drop through simulation processes. These attacks exploit the behavior of closed loop protocols such as TCP and disturb the communication process without disobeying any protocol rules, thus the detection process becomes difficult. Consequently, traffic is disrupted leading to degradation in network throughput. Through extensive simulation results that d are obtained using an industry standard scalable network simulator called NS2, impact of these attacks in terms of network throughput, overhead incurred and end-to-end delay is analyzed and used for devising detection and countermeasure. We have proposed a light-weight direct trust-based detection (DTD) algorithm which detect and remove a JellyFish node from an active communication route. Simulation results are provided, showing that in the presence of malicious-node attacks, the CBDS outperforms the existing and compared with proposed JF detection scheme in terms of packet delivery ratio and routing overhead.Mobile Adhoc Networks (MANETs) is surrounded by tons of different attacks, each with different behavior and aftermaths. One of the serious attacks that affect the normal working of MANETS is DoS Attack. A sort of DoS attack is Jellyfish attack, which is quite hard because of its foraging behavior. The Jellyfish attack is regarded as one of the most difficult attack to detect and degrades the overall network performance. In order to combat Jellyfish attack in MANETs, this paper proposes a novel technique called APD-JFAD (Accurate Prevention and Detection of Jelly Fish Attack Detection) and AODV. It is a fusion of authenticated routing-based framework for detecting attacks and Support Vector Machine. SVM is utilized for learning packet forwarding behavior. The proposed technique chooses trusted nodes in the network for performing routing of packets on the basis of hierarchical trust evaluation property of nodes. The technique is tested using NS-2 simulator against other existing techniques i.e. ABC, MABC and AR- AIDF-GFRS algorithms by various parameters such as throughput, PDR, dropped packet ratio and delay. The results prove that APD-JFAD is highly efficient in Jellyfish attack detection and also performs well as compared to other algorithms.

AODV,APD-JFAD

"Discuss the Prevention of Jelly Fish Attack by AODV and APD-JFAD in MANET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.167-176, June 2019, Available :http://www.jetir.org/papers/JETIR1907G67.pdf

"Discuss the Prevention of Jelly Fish Attack by AODV and APD-JFAD in MANET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp167-176, June 2019, Available at : http://www.jetir.org/papers/JETIR1907G67.pdf