2010
DOI: 10.1007/s11235-010-9408-x
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SafeAnon: a safe location privacy scheme for vehicular networks

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Cited by 10 publications
(10 citation statements)
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“…Then, the problems of decision delay are discussed in the next subsection. Meanwhile, the adaptive decision‐making method is also introduced . The adapted model location privacy metric is discussed in this section and also how to obtain maximum service usability constraints by location privacy.…”
Section: Proposed Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Then, the problems of decision delay are discussed in the next subsection. Meanwhile, the adaptive decision‐making method is also introduced . The adapted model location privacy metric is discussed in this section and also how to obtain maximum service usability constraints by location privacy.…”
Section: Proposed Methodsmentioning
confidence: 99%
“…First problem is that long time period during this interval may cause vehicles to receive malicious event messages. Another problem is time efficiency in decision making because pseudonym time will expire, so malicious vehicle cheats other vehicles more easily to receive malicious event messages rather than RS event messages which will have an effect on decision and adversely know the vehicle's exact identity …”
Section: Proposed Methodsmentioning
confidence: 99%
“…Among various security threats, privacy preservation in VANETs is one of the new challenges of protecting users' private information. For instance, Chen and Wei [2,10] proposed a safe, distance-based location privacy scheme called SafeAnon. By simulating vehicular mobility in a cropped Manhattan map, they evaluated the performance of the SafeAnon scheme under various conditions to show that it could simultaneously achieve location privacy as well as traffic safety.…”
Section: Introductionmentioning
confidence: 99%
“…Among various security threats, privacy preservation in VANETs is one of the new challenges of protecting users' private information. For instance, Chen and Wei proposed a safe, distance-based location privacy scheme called SafeAnon [5,6]. By simulating vehicular mobility in a cropped Manhattan map, they evaluated the performance of the SafeAnon scheme under various conditions to show that it could simultaneously achieve location privacy, as well as traffic safety.…”
Section: Introductionmentioning
confidence: 99%