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Friend recommendation service is a common and important demand for the users on various online platforms. Current studies mainly focus on making predictions with the neighborhood and path information derived from the personal relationship networks. However, the formed links do not indicate that two users are familiar with each other nor have intimate connections. Selective treatments are made according...
Privacy issues in Location-Based Services (LBSs) have gained tremendous attentions in literature over recent years. Existing approaches always fail to provide dual privacy protection on both user's location and point of interest (POI), incur endurable system overhead, and produce high quality of services, simultaneously. To address these problems, we propose a time obfuscation-based scheme, termed...
Privacy issues in Location-Based Services (LBSs) have gained tremendous attentions in literature over recent years. Existing approaches always fail to provide dual privacy protection on both user's location and point of interest (POI), incur endurable system overhead, and produce high quality of services, simultaneously. To address these problems, we propose a time obfuscation-based scheme, termed...
The ubiquity of modern mobile devices with GPS modules and Internet connectivity such as 3G/4G techniques have resulted in rapid development of Location-Based Services (LBSs). However, users enjoy the convenience provided by the untrusted LBS server at the cost of their privacy. To protect user's sensitive information against adversaries with side information, we design a personalized spatial cloaking...
In Location-Based Services (LBSs) mobile users submit location-related queries to the untrusted LBS server to get service. However, such queries increasingly induce privacy concerns from mobile users. To address this problem, we propose FGcloak, a novel fine-grained spatial cloaking scheme for privacy-aware mobile users in LBSs. Based on a novel use of modified Hilbert Curve in a particular area,...
Location-Based Service (LBS) has become a vital part of our daily life. While enjoying the convenience provided by LBS, users may lose privacy since the untrusted LBS server has all the information about users in LBS and it may track them in various ways or release their personal data to third parties. To address the privacy issue, we propose a Dummy-Location Selection (DLS) algorithm to achieve k-anonymity...
Location-Based Services (LBSs) gain increasing popularity with the development of social networks and mobile devices. The mobile users enjoy convenience by submitting their private information. Nonetheless, the users' sensitive information may be abused by an un-trusted LBS server. Privacy concerned in LBSs can be categorized into two major types: location privacy and query privacy. In this paper,...
Bacterial foraging optimization (BFO) is a relatively new bio-heuristic algorithm which is based on a metaphor of social interaction of E. coli bacteria. Although the algorithm has successfully been applied to many kinds of real word optimization problems, experimentation with complex problems reports that the basic BFO algorithm possesses a poor performance. Thus a novel bacterial foraging optimizer...
Radio Frequency Identification (RFID) has a widespread application in reality, and RFID wireless network planning is a core challenge in the deployment of RFID networks. This paper presents a new approach for optimal scheduling of RFID network based on our proposed MCPSO algorithm. RFID network planning problem is identified as a graph partitioning problem by mapping the readers in RFID network into...
A novel hybrid evolutionary system HPSONN combing an improved particle swarm optimization using multiple swarms(MCPSO) and a binary particle swarm optimization (BPSO) is proposed for joint optimization of three-layer feed-forward artificial neural networks (ANNs). In the proposed method, the topology of neural network is optimized by BPSO and connection weights are training by MCPSO. The experiment...
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