2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications 2014
DOI: 10.1109/trustcom.2014.51
|View full text |Cite
|
Sign up to set email alerts
|

Abstract: Abstract-Vehicular ad hoc networks (VANETs) are the future of vehicular technology and Traffic Information Systems. In VANETs vehicles communicate by different types of beacon messages to inform each other of their position and speed to give them a sense of traffic around them. Vehicles can also send emergency messages in case of accidents or other hazards. The very fast moving nodes have to act quickly based on these emergency messages. However, a rogue node which sends false emergency messages can wreak havo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
23
0

Year Published

2015
2015
2021
2021

Publication Types

Select...
6
2

Relationship

1
7

Authors

Journals

citations
Cited by 25 publications
(23 citation statements)
references
References 20 publications
0
23
0
Order By: Relevance
“…We extend the earlier work done in [23] significantly by extensive simulations under varying vehicular and network traffic conditions and using statistical techniques to determine false data especially in emergency messages. 2) The extensive data collected is analysed using statistical techniques and the decision to accept or reject data is based on hypothesis testing.…”
Section: A Our Contributionsmentioning
confidence: 97%
“…We extend the earlier work done in [23] significantly by extensive simulations under varying vehicular and network traffic conditions and using statistical techniques to determine false data especially in emergency messages. 2) The extensive data collected is analysed using statistical techniques and the decision to accept or reject data is based on hypothesis testing.…”
Section: A Our Contributionsmentioning
confidence: 97%
“…The data-centric approach is feasible to detect misbehaving vehicles that share false information [10,[40][41][42][43][44]. Data-centric-based solutions can be farther classified into event-based or context-based misbehavior detection.…”
Section: Related Workmentioning
confidence: 99%
“…Data-centric-based solutions can be farther classified into event-based or context-based misbehavior detection. Event-based MDS focuses on detecting false event messages, such as false congestion alerts [44], false crash notifications [38], or false emergency messages [41,45]. However, event-based MDSs are application-specific, as they covers only certain types of events, such as congestion and crash notification.…”
Section: Related Workmentioning
confidence: 99%
“…Such approach is hard to implement; this is mainly due to the nature of the neighbors list as it changes frequently. In [8], the authors use the speed, density and flow to build a model to identify malicious vehicles. Flow is calculated from speed and density, and then every vehicle compares the locally calculated flow and density with the flow and density calculated by the sender.…”
Section: Related Workmentioning
confidence: 99%