494 research outputs found
User-Defined Privacy Location-Sharing System in Mobile Online Social Networks
No full textWith the fusion of social networks and location-based services, location sharing is one of the most important services in mobile online social networks (mOSNs). In location-sharing services, users have to provide their location information to service provider. However, location information is sensitive to users, which may cause a privacy-preserving issue needs to be solved. In the existing research, location-sharing services, such as friends’ query, does not consider the attacks from friends. In fact, a user may not trust all of his/her friends, so just a part of his/her friends will be allowed to obtain the user’s location information. In addition, users’ location privacy and social network privacy should be guaranteed. In order to solve the above problems, we propose a new architecture and a new scheme called User-Defined Privacy Location-Sharing (UDPLS) system for mOSNs. In our scheme, the query time is almost irrelevant to the number of friends. We also evaluate the performance and validate the correctness of our proposed algorithm through extensive simulations
L2P2: A location-label based approach for privacy preserving in LBS
No full textThe developments in positioning and mobile communication technology have made the location-based service (LBS) applications more and more popular. For privacy reasons and due to lack of trust in the LBS providers, k-anonymity and l-diversity techniques have been widely used to preserve privacy of users in distributed LBS architectures in Internet of Things (IoT). However, in reality, there are scenarios where the locations of users are identical or similar/near each other in IoT. In such scenarios the k locations selected by k-anonymity technique are the same and location privacy can be easily compromised or leaked. To address the issue of privacy preservation, in this paper, we introduce the location labels to distinguish locations of mobile users to sensitive and ordinary locations. We design a location-label based (LLB) algorithm for protecting location privacy of users while minimizing the response time for LBS requests. We also evaluate the performance and validate the correctness of the proposed algorithm through extensive simulations
Using Location-labeling for Privacy Protection in Location-Based Services
No full textThe developments in positioning and mobile communication technology have made applications that use location-based services (LBS) increasingly popular. For privacy reasons and due to lack of trust in the LBS provider, k-anonymity and l-diversity techniques have been widely used to preserve user privacy in distributed LBS architectures. However, in reality, there exist scenarios where the user locations are identical or similar/near each other. In such a scenario the k locations selected by k-anonymity technique are the same and location privacy can be easily compromised or leaked. To address the issue of privacy protection, in this paper, we propose the concept of location-labels to distinguish mobile user locations to sensitive locations and ordinary locations. We design a location-label based (LLB) algorithm for protecting location privacy while minimizing the query response time of LBS. We also evaluate the performance and validate the correctness of the proposed algorithm through extensive simulations
Efficient location privacy algorithm for Internet of Things (IoT) services and applications
No full textLocation-based Services (LBS) have become a very important area for research with the rapid development of Internet of Things (IoT) technology and the ubiquitous use of smartphones and social networks in our daily lives. Although users can enjoy a lot of flexibility and conveniences from the LBS with IoT, they may also lose their privacy. Untrusted or malicious LBS servers with all users’ information can track users in various ways or release personal data to third parties. In this work, we first analyze the current dummy-location selection (DLS) algorithm—an efficient location privacy preservation approach and design an attack algorithm for DLS (ADLS) for test emerging IoT security. For efficiently preserving user’s location privacy, we propose a novel dummy location privacy-preserving (DLP) algorithm by considering both computational costs and various privacy requirements of different users. Extensive simulation experiments have been carried out to evaluate the efficiency of the proposed schemes. Evaluation results show that the ADLS algorithm has a high probability of identifying the user’s real location out from chosen dummy locations in the DLS algorithm. Our proposed DLP algorithm has clear advantages over the DLS algorithm in term of lower probability of revealing the user’s real location and improved computational cost and efficiency (i.e., time, speed, accuracy, and complexity) while preserve the same privacy level as DLS algorithm
Predicting Co-Author Relationship in Medical Co-Authorship Networks
No full textResearch collaborations are encouraged because a synergistic effect yielding good results often appears. However, creating and organizing a strong research group is a difficult task. One of the greatest concerns of an individual researcher is locating potential collaborators whose expertise complement his best. In this paper, we propose a method that makes link predictions in co-authorship networks, where topological features between authors such as Adamic/Adar, Common Neighbors, Jaccard’s Coefficient, Preferential Attachment, Katzb, and PropFlow may be good indicators of their future collaborations. Firstly, these topological features were systematically extracted from the network. Then, supervised models were used to learn the best weights associated with different topological features in deciding co-author relationships. Finally, we tested our models on the co-authorship networks in the research field of Coronary Artery Disease and obtained encouraging accuracy (the precision, recall, F1 score and AUC were, respectively, 0.696, 0.677, 0.671 and 0.742 for Logistic Regression, and respectively, 0.697, 0.678, 0.671 and 0.743 for SVM). This suggests that our models could be used to build and manage strong research groups
Running Head: BioThesaurus Corresponding author:
No full textBioThesaurus is a web-based system designed to map a comprehensive collection of protein and gene names to protein entries in the UniProt Knowledgebase. Currently covering more than two million proteins, BioThesaurus consists of over 2.8 million names extracted from multiple molecular biological databases according to the database cross-references in iProClass. The BioThesaurus web site allows the retrieval of synonymous names of given protein entries and the identification of protein entries sharing the same names. Availability: BioThesaurus is accessible for online searching a
Spatiotemporal Distribution Characteristics of Soil Organic Carbon in Newborn Coastal Wetlands of the Yellow River Delta Estuary
No full textThe distribution and seasonal variation of soil organic carbon (SOC) in newborn coastal wetland of the Yellow River Delta (YRD) estuary at eastern China were studied based on monitoring data in 2009 at two transects from the bank of the Yellow River to the seaside. The results showed that SOC contents of 0-60cm soil layer in transects ranged from 0.46 to 10.15gkg(-1) and average values of soil profiles ranged from 2.15 to 5.00gkg(-1). The SOC contents tended to increase from the river flood land to the salt beach, which could be accounted for the organic matters including large algae, the bodies and excretion of marine animals due to the feedback of tides. The significant difference of SOC contents at different vegetation communities was observed, while the difference of SOC in soil profiles was not obvious. The SOC contents in 0-30cm soil layers decreased with plant growth period, while in 40-60cm soil layers were relatively stable. The mean soil organic carbon density was 3.05kgCm(-2) in study region, which was much lower than that reported in other ecosystems, and its spatiotemporal variations were consistent with that of SOC content. Further analysis revealed that SOC was positively correlated with total nitrogen and clay contents. Our findings indicated that the newborn coastal wetland in the YRD should be a potential sink of SOC.The distribution and seasonal variation of soil organic carbon (SOC) in newborn coastal wetland of the Yellow River Delta (YRD) estuary at eastern China were studied based on monitoring data in 2009 at two transects from the bank of the Yellow River to the seaside. The results showed that SOC contents of 0-60cm soil layer in transects ranged from 0.46 to 10.15gkg(-1) and average values of soil profiles ranged from 2.15 to 5.00gkg(-1). The SOC contents tended to increase from the river flood land to the salt beach, which could be accounted for the organic matters including large algae, the bodies and excretion of marine animals due to the feedback of tides. The significant difference of SOC contents at different vegetation communities was observed, while the difference of SOC in soil profiles was not obvious. The SOC contents in 0-30cm soil layers decreased with plant growth period, while in 40-60cm soil layers were relatively stable. The mean soil organic carbon density was 3.05kgCm(-2) in study region, which was much lower than that reported in other ecosystems, and its spatiotemporal variations were consistent with that of SOC content. Further analysis revealed that SOC was positively correlated with total nitrogen and clay contents. Our findings indicated that the newborn coastal wetland in the YRD should be a potential sink of SOC
Condition assessment of underground corroded pipelines subject to hydrogen damage and combined internal pressure and axial compression
No full textIn this work, a 3D finite element (FE) based model was developed to assess the condition of an underground hydrogen transmission pipeline containing a corrosion defect under combined internal pressure and soil movement-induced axial compression. The use of mechanical properties of X100 pipeline steel under different hydrogen charging time models the degree of hydrogen damage in pipelines. Parameter effects, i.e., axial compressive stress, hydrogen damage, defect geometries, and pipeline diameter-to-thickness ratio, were determined. The results demonstrated that the synergistic effect of axial compression, internal pressure, corrosion, and hydrogen damage can lead to a significant decrease in the failure pressure of pipelines. The failure pressure decreased with the wall thickness reduction and increased hydrogen damage, axial compressive stress, defect length, defect depth, and pipe diameter. The competitive effect was observed between the degree of metal loss and hydrogen damage in determining the burst capacity of pipelines. In situations where the pipeline integrity was severely compromised, the failure pressure exhibited minimal reduction despite the increasing severity of hydrogen damage. The stress distribution at the defect zone was influenced by axial compressive stress but remained unaffected by hydrogen damage under normal operating conditions (i.e., an internal pressure of 10 MPa). This work is expected to help operators understand the applicability of elder and in-service pipelines for hydrogen transmission.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Safety and Security Scienc
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