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Grant: Discovery Grants Program - Individual

Concordia University

$15,000.00

Privacy-preserving RFID systems for data analysis

FY 2008-09

Summary
Radio Frequency IDentification (RFID) is a technology of automatic object identification. A typical RFID system consists of multiple tags and readers, and an infrastructure for handling the high volume of data. The tag is a small device that can be attached to an object, such as a person or a product, for the purpose of unique identification. The reader is an instrument, positioned in a strategic location, that communicates with the RFID tag. It broadcasts a radio signal to the tag, which then transmits its information back to the reader. Streams of RFID data are then stored in a database for analysis. Although RFID would be useful in a broad spectrum of applications, such as supply chain management, e-passports, and patient care and management, the uniquely identifiable tags pose a threat to privacy by tracking a person's movements or profiling an individual. Some privacy advocates have even labeled RFID as the "worst thing that ever happened to consumer privacy." Clearly, the privacy concern is an obstacle to the acceptance of RFID technology. This research program overcomes the privacy obstacle in RFID information systems and develops a series of anonymization methods to transform the underlying RFID data into a version that hides sensitive information, yet keeps it useful for data analysis. RFID data poses new challenges to traditional database, data mining, and privacy-preserving technologies due to its unique characteristics: it is time-dependent, location-dependent, and is generated in large volumes of stream data. Previous works in privacy-preserving RFID technology mainly focused on the hardware and communication protocol layers instead of the database layer, in which a large amount of data actually resides. The research results will contribute to the core data mining and privacy preservation domains, as well as the industries that employ RFID technology, sensor networks, and location-based services. The proposed research will result in a secure environment for employing RFID technology without sacrificing its information usefulness.
Program
Discovery Grants Program - Individual
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
356065-2008
Name nom
Fung, Benjamin
Department département
Engineering and Computer Science, Faculty of
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2008
Competition year année de concours
2008
Award amount
15000
Program id
RGPIN
Program nane en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
330
Committee name en
Computing and Information Sciences - A
Committee name fr
Informatique - A
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2711
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Database management
Research subject fr
Gestion de bases de données
Partie
1
Nb partie
5
Application title
Privacy-preserving RFID systems for data analysis
Keyword
NA
Application summary
Radio Frequency IDentification (RFID) is a technology of automatic object identification. A typical RFID system consists of multiple tags and readers, and an infrastructure for handling the high volume of data. The tag is a small device that can be attached to an object, such as a person or a product, for the purpose of unique identification. The reader is an instrument, positioned in a strategic location, that communicates with the RFID tag. It broadcasts a radio signal to the tag, which then transmits its information back to the reader. Streams of RFID data are then stored in a database for analysis. Although RFID would be useful in a broad spectrum of applications, such as supply chain management, e-passports, and patient care and management, the uniquely identifiable tags pose a threat to privacy by tracking a person's movements or profiling an individual. Some privacy advocates have even labeled RFID as the "worst thing that ever happened to consumer privacy." Clearly, the privacy concern is an obstacle to the acceptance of RFID technology. This research program overcomes the privacy obstacle in RFID information systems and develops a series of anonymization methods to transform the underlying RFID data into a version that hides sensitive information, yet keeps it useful for data analysis. RFID data poses new challenges to traditional database, data mining, and privacy-preserving technologies due to its unique characteristics: it is time-dependent, location-dependent, and is generated in large volumes of stream data. Previous works in privacy-preserving RFID technology mainly focused on the hardware and communication protocol layers instead of the database layer, in which a large amount of data actually resides. The research results will contribute to the core data mining and privacy preservation domains, as well as the industries that employ RFID technology, sensor networks, and location-based services. The proposed research will result in a secure environment for employing RFID technology without sacrificing its information usefulness.
Concordia University - $15,000 Grant (2008-09) | Canada Spends