Browsing by Author "KISTER, Thomas"

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    ASSIST: Access Controlled Ship Identification Streams
    (2013-02-08T04:32:24Z) CAO, Jianneng; KISTER, Thomas; XIANG, Shili; MALHOTRA, Baljeet; TAN, Wee-Juan; TAN, Kian-Lee; BRESSAN, Stéphane
    The International Maritime Organization (IMO) requires a majority of cargo and passenger ships to use the Automatic Identification System (AIS) for navigation safety and traffic control. Distributing live AIS data on the Internet can offer a global view for both operational and analytical purposes to port authorities, shipping and insurance companies, cargo owners and ship captains and other stakeholders. Yet, uncontrolled, this distribution can seriously undermine navigation safety and security and the privacy of the various stakeholders. In this paper we present ASSIST, an application system based on our recently proposed access control framework, to protect streaming data from unauthorized access. Furthermore, we have implemented ASSIST on top of StreamInsight, a commercial stream engine. The extensive experimental results show that our solution is more effective and efficient than existing approaches.
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    The Price is Right
    (2012-05-28T08:07:59Z) TANG, Ruiming; WU, Huayu; KISTER, Thomas; BRESSAN, Stephane
    Data is a modern commodity. Electronic data market places are being designed and deployed. Yet current pricing models either focus on processing or are proprietary, opaque and not conducive of a healthy commodity market dynamics. In this paper we propose a generic data pricing model that is based on minimal lineages, i.e. sets of tuples contributing to the result of a query. We show that the proposed model fulfils desirable properties such as contribution monotonicity, bounded price and arbitrage-freedom. We extend the model to the case of probabilistic databases in the X-tuple model. We propose algorithms to the compute the price of a query based on our pricing models.
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    Publishing Trajectory with Differential Privacy: A Priori vs A Posteriori Sampling Mechanisms
    (2013-04-16T03:02:38Z) SHAO, Dongxu; JIANG, Kaifeng; KISTER, Thomas; BRESSAN, Stephane; TAN, Kian Lee
    It is now possible to collect and share trajectory data for any ship in the world by various means such as satellite and VHF systems. However, the publication of such data also creates new risks for privacy breach with consequences on the security and liability of the stakeholders. Thus, there is an urgent need to develop methods for preserving the privacy of published trajectory data. In this paper, we propose and comparatively investigate two mechanisms for the publication of the trajectory of individual ships under differential privacy guarantees. Traditionally, privacy and differential privacy is achieved by perturbation of the result or the data according to the sensitivity of the query. Our approach, instead, combines sampling and interpolation. We present and compare two techniques in which we sample and interpolate (a priori) and interpolate and sample (a posteriori), respectively. We show that both techniques achieve a $(0, \delta)$ form of differential privacy. We analytically and empirically, with real ship trajectories, study the privacy guarantee and utility of the methods.