Protecting privacy for distance and rank based group nearest neighbor queries

World Wide Web - This paper proposes a novel approach to safeguarding location privacy for GNN (group nearest neighbor) queries. Given the locations of a group of dispersed users, the GNN query...     

Interaction between chronic arsenic exposure via drinking water and plasma lactate dehydrogenase activity

Arsenic is a potent environmental pollutant that has caused one of the largest public health poisonings in the history of human civilization, affecting tens of millions of people worldwide especially in Bangladesh. Lactate dehydrogenase (LDH) in blood plays an important role in predicting cell or organ damage and as an important clue to the diagnosis of a variety of cancers. However, effect of chronic arsenic exposure on the LDH level in blood has not yet been documented. Since the chronic arsenic exposure is associated with organ damages and multi-site cancers, this research aimed at assaying the plasma level of LDH activity in the population who were exposed to arsenic chronically in Bangladesh. A total of 185 individuals living in arsenic-exposed areas and 121 individuals living in non-exposed area in Bangladesh were recruited as study subjects. Arsenic content in drinking water, hair and nails were estimated by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) and LDH activity was assayed by a spectrophotometer. Significant increase in LDH activity was observed with increasing concentrations of arsenic in water, hair and nails. Further, the study subjects were split into four groups based on the three ways of each exposure metrics (water, hair and nail arsenic concentrations) where the study subjects in the non-exposed area were used as a reference (lowest exposure) group. LDH activity was found to be increased in the higher exposure groups of water and hair arsenic concentrations. LDH activity was also increased at low to medium exposure groups of nail arsenic concentrations.Thus, the elevated plasma LDH activity might be helpful for the early prognosis of organ or tissue damage in the individuals who were exposed to arsenic chronically.     

Serial Passaging of RAW 264.7 Cells Modulates Intracellular AGE Formation and Downregulates RANKL-Induced In Vitro Osteoclastogenesis

The passage number of cells refers to the number of subculturing processes that the cells have undergone. The effect of passage number on morphological and phenotypical characteristics of cells is of great importance. Advanced glycation end products have also been associated with cell functionality and characteristics. Murine monocyte RAW 264.7 cells differentiate into osteoclasts upon receptor activation caused by nuclear factor-kappa-Β ligand (RANKL) treatment. This study aims to identify the role of passage number on intracellular advanced glycation end products (AGEs) formation and osteoclastogenic differentiation of RAW 264.7 cells. Western blotting was performed to check intracellular AGE formation along with fluorometric analysis using a microplate reader. Tartrate-resistant acid phosphatase (TRAP) staining was performed to check osteoclastogenic differentiation, and qPCR was realized to check the responsible mRNA expression. Immunofluorescence was used to check the morphological changes. Intracellular AGE formation was increased with passaging, and the higher passage number inhibited multinucleated osteoclastogenic differentiation. Osteoclastogenic gene expression also showed a reducing trend in higher passages, along with a significant reduction in F-actin ring size and number. Lower passages should be used to avoid the effects of cell subculturing in in vitro osteoclastogenesis study using RAW 264.7 cells.     

Reliable and Efficient Distributed Checkpointing System for Grid Environments

In Fine-Grained Cycle Sharing (FGCS) systems, machine owners voluntarily share their unused CPU cycles with guest jobs, as long as their performance degradation is tolerable. However, unpredictable evictions of guest jobs lead to fluctuating completion times. Checkpoint-recovery is an attractive mechanism for recovering from such “failures”. Today’s FGCS systems often use expensive, high-performance dedicated checkpoint servers. However, in geographically distributed clusters, this may incur high checkpoint transfer latencies. In this paper we present a distributed checkpointing system called Falcon that uses available disk resources of the FGCS machines as shared checkpoint repositories. However, an unavailable storage host may lead to loss of checkpoint data. Therefore, we model the failures of a storage host and develop a prediction algorithm for choosing reliable checkpoint repositories. We experiment with Falcon in the university-wide Condor testbed at Purdue and show improved and consistent performance for guest jobs in the presence of irregular resource availability.     

Countering overlapping rectangle privacy attack for moving kNN queries

An important class of LBSs is supported by the moving k nearest neighbor (MkNN) query, which continuously returns the k nearest data objects for a moving user. For example, a tourist may want to observe the five nearest restaurants continuously while exploring a city so that she can drop in to one of them anytime. Using this kind of services requires the user to disclose her location continuously and therefore may cause privacy leaks derived from the user's locations. A common approach to protecting a user's location privacy is the use of imprecise locations (e.g., regions) instead of exact positions when requesting LBSs. However, simply updating a user's imprecise location to a location-based service provider (LSP) cannot ensure a user's privacy for an MkNN query: continuous disclosure of regions enable LSPs to refine more precise location of the user. We formulate this type of attack to a user's location privacy that arises from overlapping consecutive regions, and provide the first solution to counter this attack. Specifically, we develop algorithms which can process an MkNN query while protecting the user's privacy from the above attack. Extensive experiments validate the effectiveness of our privacy protection technique and the efficiency of our algorithm.     

Trip planning queries with location privacy in spatial databases

Privacy has become a major concern for the users of location-based services (LBSs) and researchers have focused on protecting user privacy for different location-based queries. In this paper, we propose techniques to protect location privacy of users for trip planning (TP) queries, a novel type of query in spatial databases. A TP query enables a user to plan a trip with the minimum travel distance, where the trip starts from a source location, goes through a sequence of points of interest (POIs) (e.g., restaurant, shopping center), and ends at a destination location. Due to privacy concerns, users may not wish to disclose their exact locations to the location-based service provider (LSP). In this paper, we present the first comprehensive solution for processing TP queries without disclosing a user’s actual source and destination locations to the LSP. Our system protects the user’s privacy by sending either a false location or a cloaked location of the user to the LSP but provides exact results of the TP queries. We develop a novel technique to refine the search space as an elliptical region using geometric properties, which is the key idea behind the efficiency of our algorithms. To further reduce the processing overhead while computing a trip from a large POI database, we present an approximation algorithm for privacy preserving TP queries. Extensive experiments show that the proposed algorithms evaluate TP queries in real time with the desired level of location privacy.