Reference : CAPS: Context-Aware Privacy Scheme for VANET Safety Applications
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/28898
CAPS: Context-Aware Privacy Scheme for VANET Safety Applications
English
Emara, Karim Ahmed Awad El-Sayed mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Woerndl, Wolfgang [> >]
Schlichter, Johann [> >]
2015
ACM Wisec 15
Yes
International
9781450336239
8th ACM Conference on Security & Privacy in Wireless and Mobile Networks
June 2015
[en] location privacy ; context-aware privacy ; forward collision warning
[en] Preserving location privacy in vehicular ad hoc networks
(VANET) is an important requirement for public accep-
tance of this emerging technology. Many privacy schemes
concern changing pseudonyms periodically to avoid linking
messages. However, the spatiotemporal information con-
tained in beacons makes vehicles traceable and the driver’s
privacy breached. Therefore, the pseudonym change should
be performed in a mix-context to discontinue the spatial
and temporal correlation of subsequent beacons. Such mix-
context is commonly accomplished by using a silence period
or in predetermined locations (e.g., mix-zone). In this pa-
per, we propose a location privacy scheme that lets vehicles
decide when to change its pseudonym and enter a silence
period and when to exit from it adaptively based on its con-
text. In this scheme, a vehicle monitors the surrounding
vehicles and enters silence when it finds one or more neigh-
bors silent. It resumes beaconing with a new pseudonym
when its actual state is likely to be mixed with the state of
a silent neighbor. We evaluate this scheme against a global
multi-target tracking adversary using simulated and realistic
vehicle traces and compare it with the random silent period
scheme. Furthermore, we evaluate the quality of service of
a forward collision warning safety application to ensure its
applicability in safety applications. We measure the quality
of service by estimating the probability of correctly identify-
ing the fundamental factors of that application using Monte
Carlo analysis.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/28898

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