Marios Vodas

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Existing approaches for privacy-aware mobility data sharing aim at publishing an anonymized version of the mobility dataset, operating under the assumption that most of the information in the original dataset can be disclosed without causing any privacy violations. In this paper, we assume that the majority of the information that exists in the mobility(More)
We present a system that combines intelligent online tracking with complex event recognition against streaming positions relayed from numerous vessels. Given the vital importance of maritime safety to the environment, the economy, and in national security, our system leverages the real-time acquisition of vessel activity with geographical and other static(More)
Mobility data sources feed larger and larger trajectory databases nowadays. Due to the need of extracting useful knowledge patterns that improve services based on users' and customers' behavior, querying and mining such databases has gained significant attention in recent years. However, publishing mobility data may lead to severe privacy violations. In(More)
We present a system for online monitoring of maritime activity over streaming positions from numerous vessels sailing at sea. It employs an online tracking module for detecting important changes in the evolving trajectory of each vessel across time, and thus can incrementally retain concise, yet reliable summaries of its recent movement. In addition, thanks(More)
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