Kok-Seng Wong

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Similarity coefficients (also known as coefficients of association) are important measurement techniques used to quantify the extent to which objects resemble one another. Due to privacy concerns, the data owner might not want to participate in any similarity measurement if the original dataset will be revealed or could be derived from the final output.(More)
Finding similarities between two datasets is an important task in many research areas, particularly those of data mining, information retrieval, cloud computing, and biometrics. However, maintaining data protection and privacy while enabling similarity measurements has become a priority for data owners in recent years. In this paper, we study the design of(More)
Advances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people's life and living styles. However, collecting and storing user's data in the smart environments pose severe privacy concerns because these data may contain sensitive information about the subject. Hence, privacy protection(More)