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A weighted K-member clustering algorithm for K-anonymization
As a representative model for privacy preserving data publishing, K-anonymity has raised a considerable number of questions for researchers over the...
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Distributed L-diversity using spark-based algorithm for large resource description frameworks data
Privacy protection issues for resource description frameworks (RDFs) have emerged over the use of public government open data and the healthcare data...
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Graph Matching Based Privacy-Preserving Scheme in Social Networks
The increasing popularity of social networks has inspired recent research to explore social graphs for data mining. Because social graph data...
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Video in 10 Bits: Few-Bit VideoQA for Efficiency and Privacy
In Video Question Answering (VideoQA), answering general questions about a video requires its visual information. Yet, video often contains redundant...
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Path-Preserving Anonymization for Inter-domain Routing Policies
The Internet consists of tens of thousands of autonomous systems (ASes), which exchange routing information through policy-based routing protocols,...
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Harmonic Group Mix: A Framework for Anonymous and Authenticated Broadcast Messages in Vehicle-to-Vehicle Environments
Nowadays Vehicle-to-Vehicle communication (V2V) plays an increasingly important role, not only in terms of safety, but also in other areas of...
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Limiting Disclosure by Hiding the Identity
This chapter begins the examination of techniques that are designed to limit disclosure (rather than exposure). In particular, it focuses on...
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Shared-Dining: Broadcasting Secret Shares Using Dining-Cryptographers Groups
We introduce a combination of Shamir’s secret sharing and dining-cryptographers networks, which provides...
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An Optimization-Based Decomposition Heuristic for the Microaggregation Problem
Given a set of points, the microaggregation problem aims to find a clustering with a minimum sum of squared errors (SSE), where the cardinality of...
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Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications
In line with the concept of Smart cities and Smart World, there have been bewildering developments in the field of Internet of Things (IoT) and Big...
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Guide to Data Privacy Models, Technologies, Solutions
Data privacy technologies are essential for implementing information systems with privacy by design.Privacy technologies clearly are needed for...
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Privacy preserving data sharing and analysis for edge-based architectures
In this paper, we present a framework for privacy preserving collaborative data analysis among multiple data providers acting as edge of a cloud...
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Anonymizing Machine Learning Models
There is a known tension between the need to analyze personal data to drive business and the need to preserve the privacy of data subjects. Many data...
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Security- and Privacy-Aware IoT Application Placement and User Assignment
Applications for the Internet of Things (IoT) may use, beyond the IoT devices themselves, also edge and cloud resources. Thus, the modules of an...
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Preliminaries
This chapter provides a fundamental understanding regarding privacy-preserving technologies, followed by deep learning. We introduce the classical...
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Protecting query privacy with differentially private k-anonymity in location-based services
Nowadays, location-based services (LBS) are facilitating people in daily life through answering LBS queries. However, privacy issues including location ...
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Remodeling: improved privacy preserving data mining (PPDM)
The data provided by individuals and various organizations while using internet applications and mobile devices are very useful to generate solutions...
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Not a Free Lunch, But a Cheap One: On Classifiers Performance on Anonymized Datasets
The problem of protecting datasets from the disclosure of confidential information, while published data remains useful for analysis, has recently...
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K-Anonymity Algorithm Based on Improved Clustering
K-anonymity is the most widely used technology in the field of privacy preservation. It has a good performance particularly in protecting data...