Keamanan Jaringan Menggunakan Unified Threat Management Pada Server Berbasiskan Linux

Heru, Bambang; Benny, Benny; Defendy, Defendy; Hento, Wahyu

doi:10.21512/commit.v1i1.467

Cited by 1 publication

(3 citation statements)

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“…In the route of discovery process, the first RREP message arrived is ignored and the second RREP is chosen to establish the routing path. This mechanism Cite this article as: E. Mustikawati, D. Perdana, and R. M. Negara, "Network Security Analysis in Vanet Against Black Hole and Jelly Fish Attack with Intrusion Detection System Algorithm", CommIT (Communication & Information Technology) Journal 11 (2), 77-83, 2017.…”

Section: E Intrusion Detection Systemmentioning

confidence: 99%

“…VANETs is a promising approach to Intelligent Transportation System (ITS) [1]. A network system that connects to the Internet requires better protection in usage because it has a high threat level [2]. Ad-hoc network has a decentralized architecture, and algorithm in ad-hoc network relies on the participation of cooperative node on the network VANET.…”

Section: Introductionmentioning

confidence: 99%

“…In this research, to prevent the attacks, IDSAODV is used as prevention algorithm for both attacks in two scenarios. The vehicular environment is modeled in Cite this article as: E. Mustikawati, D. Perdana, and R. M. Negara, "Network Security Analysis in Vanet Against Black Hole and Jelly Fish Attack with Intrusion Detection System Algorithm", CommIT (Communication & Information Technology) Journal 11 (2), 77-83, 2017. highway road, Jakarta-Cikampek toll road.…”

Section: Introductionmentioning

confidence: 99%

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Network Security Analysis in Vanet Against Black Hole and Jellyfish Attack with Intrusion Detection System Algorithm

Mustikawati

Perdana

Negara

2017

CommIT (Communication and Information Technology) Journal

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VANET is the key to the Intelligent Transportation Systems (ITS), where vehicles can communicate with others to exchange information in real time. VANET is an ad-hoc that has no fixed infrastructure and rapidly changing network topology. As the result, the network is insecure and vulnerable to various attacks both from within and outside the network. This research analyzes AODV routing protocol comparing the conditions without the attacks and with the attacks with the of black hole and jellyfish using the algorithm of Intrusion Detection System with the number of nodes changing from 10 to 100 nodes at the change speeds of 70, 80, 90, 100, 110, and 120 km/h. This research is simulated using Network Simulator 2 to model the network and ONESimulator to model node mobility. The analyzed QoS parameters are packet delivery ratio (PDR), throughput, and end-to-end delay. The results of the simulation show that changing the number of nodes and node velocity affects the performance in the network. On the number of nodes scenario with attacks, the average value of PDR decreases by 48.03%, throughput decreases by 50.23%, and delay, for black hole, decreases by 80.18% but increases by 47.87% for jellyfish. Whereas in the node velocity scenario, the average values of PDR, throughput, and delay decrease by 58.52%, 60.34%, 13.81% for blackhole attack, respectively. However, the delay increases by 123.91% for jellyfish attack.

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Section: E Intrusion Detection Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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