Abstract. A trajectory is the time-stamped path of a moving entity through space. Given a set of trajectories, this paper proposes new conceptual definitions for a spatio-temporal pattern named Herd and four types of herd evolvements: expand, join, shrink, and leave based on the definition of a related term flock. Herd evolvements are identified through measurements of Precision, Recall, and F-score. A graph-based representation, Herd Interaction Graph, or Herding, for herd evolvements is described and an algorithm to generate the graph is proposed and implemented in a Geographic Information System (GIS) environment. A data generator to simulate herd movements and their interactions is proposed and implemented as well. The results suggest that herds and their interactions can be effectively modeled through the proposed measurements and the herd interaction graph from trajectory data.
Location-based social network (LBSN) requires answering a variety of queries related to user locations. In this paper, we investigate issues in performing secure multi-party computation in LBNS and discuss some of the challenges and problems associated with it. In particular, we look at the group nearest neighbor queries and discuss the privacy leakage problem in two party group nearest neighbor computation. We elucidate the attack model and propose a privacy leakage index to measure the impact. We perform experiments to show the privacy leakage problem and suggest a solution to deal with this problem.
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