Date post: | 26-Dec-2015 |
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-Himali Jani-Cong Cheng-Shuang Wu
A Vehicular Ad Hoc Networks Intrusion Detection System Based on
BUSNet
What is VANETs?
Vehicular Ad hoc NETworks (VANETs) , is a special case of Mobile Ad hoc NETworks (MANETs).
Cars as routers or nodes. 100-300 meters range. As cars fall out of the signal range
and drop out of the network
Security Challenges in VANETs
Security challenges: -Mobility-Dynamic topology-Open wireless medium-No use of secure routing protocols because of insider attack
Properties of this method includes: IDS architecture is hierarchical and Detection algorithm can study normal behavior of network through a neural network so works intelligently
Intrusion Defense
First line of defense: intrusion prevention techniques, such as authentication and encryption
Second line of defense: Intrusion Detection,
Which determines whether unauthorized users are attempting to access, have already accessed, or have compromised the network.
Related work
Two types IDS: monitoring based and clustering based Monitoring: watchdog to detect misbehaving nodes
and pathrater to help avoid these nodes THE CONFIDANT: cooperation of nodes fairness in
dynamic ad-hoc network CORE:only positive reports passed unlike confidant Clustering: head monitoring agent and detection
agent Choosing cluster heads based on connectivity,
proximity, resistance to compromise accessibility, processing and storage power
UAV_MBN: UAV and MBN ZBIDS: Zone based intrusion detection system
BUSNet
A virtual mobile backbone infrastructure constructed using public buses.
Virtual infrastructure: Does not require the setup of any physical infrastructure.
can be deployed rapidly into any metropolitan environment with regular public bus service.
Mobile : the main nodes that form the BUSNet backbone are moving buses.
Backbone infrastructure : used to provide a reliable data bus for vehicles to interact with each other over a metropolitan coverage if needed.
BUSNet
IDS based on BUSNet
Three layers: 1. VANETs 2. Buses 3. Access points: road side communication infrastructure ID technique in two categories : 1. Misuse detection: Can find known attacks effectively by
signature comparing 2. Anomaly detection : Effective in finding out unknown
attacks by looking for anomaly means any deviation from normal behavior. But gives more false alarm
Anomaly detection main parts: Feature selection, model of normal behavior and comparison (Explain all of them)
Feature selection : features from routing control messages and data packets. Bus collects the data and transfers to access points
Hierarchical Architecture of BUSNet
Experiments
Experiments
During the simulation
time, Attacks happened 4
times as follows:1. 20-40
2. 80-1003. 140-1804. 260-280
Neural network training and detection results
Detection error: AODV vs. DSDV vs. DSR
Thank You