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The article is devoted to the search for ways to protect the data privacy for Internet of things. Different technologies and algorithms of privacy protection are considered, their computing and energy intensity is investigated. Prototyping is performed on the FPGA of the Internet of things. Searching for ways to minimize energy consumption and computing costs of the Internet of things with algorithms...
The attribute based signature scheme could verify the signature by the attribute instead of public key. But, a large number of bilinear operations are concentrated in the verification process, so the amount of computation required for signature verification is much larger than that of signature generation. To solve this problem, this paper proposed an attribute based signature scheme with aided-verification,...
The accuracy of user location information is inversely proportional to the user's privacy preserving degree k, and is proportional to quality of query service. In order to balance the conflict between privacy preserving security and query quality caused by the accuracy of location information, A clustering algorithm aiming at eliminating outliers based on k-anonymity location privacy preserving model...
Recent large-scale deployments of differentially private algorithms employ the local model for privacy (sometimes called PRAM or randomized response), where data are randomized on each individual's device before being sent to a server that computes approximate, aggregate statistics. The server need not be trusted for privacy, leaving data control in users' hands. For an important class of convex optimization...
Differential privacy (DP) has emerged as a popular standard for privacy protection and received great attention from the research community. However, practitioners often find DP cumbersome to implement, since it requires additional protocols (e.g., for randomized response, noise addition) and changes to existing database systems. To avoid these issues we introduce Explode, a platform for differentially...
Privacy preserving data mining have been studied widely on static data. Static algorithms are not suitable for streaming data. This imposes the study of new algorithms for privacy preserving that cope with data streams characteristics. Recently, effective anonymization algorithms have been studied on centralized data streams. In this paper we propose an approach for anonymizing distributed data streams...
Social media sharing is one of the most popular social interactions in online social networks (OSNs). Due to the diverse networking conditions and various privacy requirements of OSN users, scalable media sharing has become a promising paradigm. It allows a media data distributor to share a media content of different qualities with different data consumers. To guarantee user privacy in scalable media...
Location-Based Service (LBS) is one of the fundamental and central functionalities of mobile social networks. Since users usually have to report their locations to the LBS providers while using services, the protection of user's location privacy poses a critical challenge. Although many existing approaches can preserve user's location privacy effectively, most of them must include and use the user's...
Solving large-scale systems of linear equations (L-SLE) is a common scientific and engineering computational task. But such problem involves enormous computing resources, which is burdensome for the resource-limited clients. Cloud computing enables computational resource-limited clients to economically outsource such problems to the cloud server. However, outsourcing LSLE to the cloud brings great...
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...
This paper presents a comparison between symmetric and asymmetric key encryption algorithm based decryption mixnets through simulation. Mix-servers involved in a decryption mixnet receive independently and repeatedly encrypted messages as their input, then successively decrypt and shuffle them to generate a new altered output from which finally the messages are regained. Thus mixnets confirm unlinkability...
In road networks, k-Range Nearest Neighbor (kRNN) queries locate the k-nearest neighbors for every point on the road segments that are within a given query region, based on the network distance. This is an important task, because the user's location information may not be accurate, furthermore, users may be unwilling to reveal their exact location for privacy reasons. Therefore, in this specific situation,...
Location-based Services (LBSs) via mobile handled devices have been subject to major privacy concerns for users. Currently, most of the existing works concerning the continuous LBS queries mainly focus on users' privacy demands with little consideration of the service of quality (QoS). In this paper, we propose a Demand-Aware Location Protection scheme (DALP) for continuous LBS requests, allowing...
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 has been widely used to guide the user with real time information. The efficient query processing and preserving the privacy of the user is a key challenge in these applications. There have been many researches for anonymity in the spatial network by generating cloaking region in the Road networks and a K-NN algorithm is used for processing query in this region. If the same...
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,...
Positioning capabilities offered in modern mobile devices enable usage of location-based services. Privacy and security is of great importance for related applications. We present a framework that allows conducting research on anonymity techniques in a real-life environment using smartphones. The proposed solution also includes logging mechanisms that facilitate positioning research dataset development...
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