Jung-Ho Um

An Advanced Cloaking Algorithm Using Hilbert Curves for Anonymous Location Based Service

Location Based Services (LBSs) have recently attracted much attention due to the advancement of GPS facilitates. In LBS, the private and confidential information of user may disclose to others since LBS need a user’s location. To protect the privacy of users, many cloaking algorithms have been proposed to hide user’s actual location. The existing Hilbert cloaking algorithm support location privacy, but it has a drawback that it extends a cloaking region inefficiently due to the dimensionality reduction. In this paper, we propose a new cloaking algorithm which can avoid the unnecessary extension of cloaking region. Our algorithm optimizes the generation of a cloaking region by storing adjacent cell information being not connected by Hilbert curve. From experimental results, it is shown that our proposed cloaking algorithm outperforms the existing Hilbert algorithm.

A new trajectory indexing scheme for moving objects on road networks

In this paper, we propose an efficient signature-based indexing scheme for efficiently dealing with the trajectories of current moving objects on road networks. We show that our indexing scheme achieves much better trajectory retrieval performance than the existing trajectory indexing schemes, such as TB-tree, FNR-tree and MON-tree.

TMN-tree: New Trajectory Index Structure for Moving Objects in Spatial Networks

Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks, like FNR-tree and MON-tree. But, because both FNR-tree and MON-tree store the moving objects segment, they can not support a spatio-temporal range query and a similar trajectory query. In this paper, we propose an efficient trajectory index structure for moving objects, named TMN-Tree (Trajectory of Moving objects on Network Tree), which can support not only a range query but also a similar trajectory query. In addition, we present query processing algorithms to support them. Main advantages of the TMN-tree are as follows; i) storing temporal data and spatial data in separate structures, ii) preserving the entire trajectories of moving objects, and iii) providing efficient trajectory-based query processing algorithms. Finally, we show that our trajectory index structure outperforms existing trajectory index structures, like FNR-Tree and MON-Tree.

A New Cloaking Method Supporting both K-anonymity and L-diversity for Privacy Protection in Location-Based Service

In Location-Based Services (LBSs), users send location-based queries to LBS servers along with their exact locations, but the location information of the users can be misused by adversaries. In this regard, there must be a mechanism which can deal with the privacy protection of the users. In this paper, we propose a cloaking method considering both K-anonymity and L-diversity. Our cloaking method creates a minimum cloaking region by finding L number of buildings (L-diversity) and then finds K number of users (K-anonymity). To support it, we use R*-tree based index structures as well as efficient filtering techniques to generate a minimum cloaking region. Finally, we show from our performance analysis that our cloaking method outperforms the existing grid-based cloaking method in terms of the size of cloaking regions and cloaking region creation time.

A New Grid-Based Cloaking Algorithm for Privacy Protection in Location-Based Services

In Location-Based Services (LBSs), users send location-based queries to LBS servers along with their exact locations, but the location information of the users can be misused by adversaries. For this, a mechanism to deal with the users’ privacy protection is required. In this paper, we propose a new cloaking algorithm for privacy protection in LBSs. Our cloaking algorithm can support both k-anonymity and l-diversity. That is, it first creates a minimum cloaking region by finding l buildings (l-diversity) and then finds k users (k-anonymity). To generate the minimum cloaking region efficiently, we make use of a grid structure for storing buildings and users as well as a pruning technique for reducing unnecessary computation. Finally, we show from our performance analysis that our cloaking algorithm outperforms the existing grid-based cloaking algorithm, in terms of the size of cloaking regions, their creation time and query processing time based on them.

New Range and k-NN Query Processing Algorithms Using Materialization Technique on Spatial Network

In this paper, we propose new query processing algorithms for typical spatial queries in SNDB, such as range search and k nearest neighbors (k-NN) search. Our two query processing algorithms can reduce the computation time of network distance between a pair of nodes and the number of disk I/Os required for accessing nodes by using a materialization-based technique with the shortest network distances of all the nodes in the spatial network. Thus, our query processing algorithms improve the existing efficient k-NN (INE) and range search (RNE) algorithms proposed by [1]. It is shown that our range query processing algorithm achieves about up to one of magnitude better performance than the RNE and our k- NN query processing algorithm achieves about up to 150% performance improvements over INE.

An efficient trajectory index structure for moving objects in location-based services

Because moving objects usually moves on spatial networks, efficient trajectory index structures are required to gain good retrieval performance on their trajectories. However, there has been little research on trajectory index structure for spatial networks, like road networks. In this paper, we propose an efficient trajectory index structure for moving objects in Location-based Services (LBS). For this, we design our access scheme for efficiently dealing with the trajectories of moving objects on road networks. In addition, we provide both an insertion algorithm to store the initial information of moving object trajectories and one to store their segment information. We also provide a retrieval algorithm to find a set of moving objects whose trajectories match the segments of a query trajectory. Finally, we show that our trajectory access scheme achieves about one order of magnitude better retrieval performance than TB-tree.

A new cloaking algorithm using Hilbert curves for privacy protection

Due to the advancement of GPS facilitates, the use of Location Based Service (LBS) has recently been increased rapidly. Since LBS needs the location of user, the private and confidential information of user may disclose to others. To protect the privacy of users, many cloaking algorithms have been proposed to hide users actual location. The existing Hilbert cloaking algorithm shows its high accuracy in terms of location privacy, but it has a drawback that it extends a cloaking region inefficiently due to the dimensionality reduction. In this paper, we propose a new cloaking algorithm which can avoid the unnecessary extension of cloaking region. Our algorithm optimizes the generation of a cloaking region by storing adjacent cell information being not connected by Hilbert curve. From experimental results, it is shown that our proposed cloaking algorithm outperforms the existing Hilbert algorithm.

Fault-Tolerant Cluster Management Tool for Supporting Nonstop of Cluster DBMS

In this paper, we design and implement a fault-tolerant cluster management tool which can monitor the status of the nodes in a cluster DBMS (Database Management System) as well as the status of the various DBMS instances at a given node. Based on the monitoring, our cluster management tool can provide an intelligent fail-over mechanism for dealing with multiple node failures in a cluster DBMS, thus making its fault-tolerance possible when combined with a load balancer. We implement our cluster management tool by using Linux virtual server 0.81 as a load balancer and iBASE/Cluster as a cluster-based DBMS, under a cluster system with four server nodes. It is shown that the sensing and recovery time of our cluster management tool for the iBASE/Cluster is about 2 seconds while that of OCMS for Oracle DBMS is more than 20 seconds. Finally we show that our cluster management tool can support the nonstop and self-managing of cluster DBMS with its intelligent fail-over mechanism even in case of multiple node failures.