scholarly journals An Intrusion Detection System against Black Hole Attacks on the Communication Network of Self-Driving Cars

2015 ◽  
Author(s):  
Anna Gruebler ◽  
Klaus D. McDonald-Maier ◽  
Khattab M. Ali Alheeti
Keyword(s):  
Communication Network ◽  
Black Hole ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Self Driving Cars

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

2017 ◽  
Vol 11 (2) ◽  
pp. 77
Author(s):  
Elsa Mustikawati ◽  
Doan Perdana ◽  
Ridha Muldina Negara
Keyword(s):  
Black Hole ◽  
Intrusion Detection ◽  
Intelligent Transportation Systems ◽  
Intrusion Detection System ◽  
Detection System ◽  
Security Analysis ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Node Mobility ◽  
Network Simulator

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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