One More Accuracy k-Anonymity Framework for LBS
نویسندگان
چکیده
منابع مشابه
Nonexposure Accurate Location K-Anonymity Algorithm in LBS
This paper tackles location privacy protection in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. Location cloaking has been proposed and well studied to protect user privacy. It blurs the user's accurate coordinate and replaces it with a well-shaped cloaked region. However, to...
متن کاملA reciprocal framework for spatial K-anonymity
Spatial K-anonymity (SKA) exploits the concept of K-anonymity in order to protect the identity of users from location-based attacks. The main idea of SKA is to replace the exact location of a user U with an anonymizing spatial region (ASR) that contains at least K-1 other users, so that an attacker can pinpoint U with probability at most 1/K. Simply generating an ASR that includes K users does ...
متن کاملOn the Formation of Historically k-Anonymous Anonymity Sets in a Continuous LBS
Privacy preservation in location based services (LBS) has received extensive attention in recent years. One of the less explored problems in this domain is associated with services that rely on continuous updates from the mobile object. Cloaking algorithms designed to hide user locations in single requests perform poorly in this scenario. The historical k-anonymity property is therefore enforce...
متن کاملk-Anonymity
To protect respondents’ identity when releasing microdata, data holders often remove or encrypt explicit identifiers, such as names and social security numbers. De-identifying data, however, provide no guarantee of anonymity. Released information often contains other data, such as race, birth date, sex, and ZIP code, that can be linked to publicly available information to re-identify respondent...
متن کاملApproximation Algorithms for k-Anonymity
We consider the problem of releasing a table containing personal records, while ensuring individual privacy and maintaining data integrity to the extent possible. One of the techniques proposed in the literature is k-anonymization. A release is considered k-anonymous if the information corresponding to any individual in the release cannot be distinguished from that of at least k − 1 other indiv...
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ژورنال
عنوان ژورنال: Mobile Information Systems
سال: 2019
ISSN: 1574-017X,1875-905X
DOI: 10.1155/2019/9297181