移动社交网络中的用户隐私保护研究

发布时间：2023-11-04 08:23

　　随着移动设备及社交网络技术的不断发展,移动社交网络已经变成一种在国内、外移动用户之间快速增长的应用。借助于智能手机、平板电脑等现代智能设备,移动用户可以通过访问苹果应用商店或者谷歌应用商店等下载诸多应用软件。通过各种不同的应用软件,从而1)享受各种服务运营商所提供的服务信息,例如,基于位置服务信息;2)通过短距离通信技术,如蓝牙等实现与周围用户的相互通信,以共享彼此间的信息、视频等,例如基于临近度的移动社交网络。为了享受此类服务,用户通常需要泄漏其位置、兴趣爱好或其他相关信息给不可信的第三方(例如基于位置服务中的服务器)或者周围其他用户作为第一步。然而由于此类服务器及周边用户往往可以获取用户的相关信息,包括用户身处何时何地,希望获取什么样的请求,正在做什么等。拥有了这些信息,用户可能被跟踪,或者其信息被泄露给一些恶意第三方。因此,对用户隐私的保护刻不容缓。现有方案大都依赖可信第三方,或者难以为用户提供满足细粒度的隐私保护策略。本文提出了一系列解决方案,为移动社交网络用户提供高效的隐私保护,尤其是基于位置服务和基于用户临近度的移动社交网络。本文主要的贡献如下:1)本章指出了背景信息在基于...

【文章页数】：151 页

【学位级别】：博士

【文章目录】：
摘要
ABSTRACT
List of Common Notation
List of Abbreviations
Chapter 1 Introduction
    1.1 Background
        1.1.1 Overviews of LBSs and PMSNs
        1.1.2 Architectures of LBSs and PMSNs
    1.2 Related Works
        1.2.1 Privacy Threats in LBSs
        1.2.2 Metrics for Location Privacy
        1.2.3 Protecting Location Privacy
        1.2.4 User Privacy in Proximity-Based Mobile Social Networks
    1.3 Motivations
        1.3.1 Reliance on the Trusted Third Parties
        1.3.2 Ignorance on the Side Information
        1.3.3 Ignorance on the Size of Cloaking Region
        1.3.4 Ignorance on the Priority Information
        1.3.5 Reliance on the Heavy Cryptographic Tools
    1.4 Objectives and Main Contributions
    1.5 Organization
Chapter 2 Preliminaries
    2.1 Preliminaries in Location-Based Services
        2.1.1 Side Information
        2.1.2 Cloaking Region
        2.1.3 Hilbert Curve
        2.1.4 Privacy Metric
        2.1.5 Adversary Models
    2.2 Preliminaries in Private Matching Problems
        2.2.1 Commutative Encryption Function
        2.2.2 Bloom Filter
Chapter 3 Achieving k-anonymity in Privacy-Aware Location-Based Services
    3.1 Motivation
    3.2 Dummy-Location Selection Algorithms
        3.2.1 The DLS Algorithm
        3.2.2 The Enhanced-DLS Algorithm
        3.2.3 Security Analysis
        3.2.4 Implementation Issues
    3.3 Performance Evaluations
        3.3.1 Simulation Setup
        3.3.2 Evaluation Results
    3.4 Conclusion
Chapter 4 A Fine-Grained Spatial Cloaking Scheme in Location-Based Services
    4.1 Motivation
    4.2 Our Fine-Grained Cloaking Scheme
        4.2.1 System Architecture
        4.2.2 Modified Hilbert Curve Constructing Algorithm
        4.2.3 Privacy-Aware Dummy Selecting Algorithm
        4.2.4 Fine-Grained Local Replacement Algorithm
        4.2.5 Security Analysis
    4.3 Performance Evaluations
        4.3.1 Simulation Setup
        4.3.2 Evaluation Results
    4.4 Conclusion
Chapter 5 Encounter-Based Privacy-Aware Scheme for Location-Based Services
    5.1 Motivation
    5.2 Our Proposed EPS
        5.2.1 Basic Concepts
        5.2.2 System Overview
        5.2.3 Protocol Details
        5.2.4 Security Analysis
    5.3 Performance Evaluations
        5.3.1 Simulation Setting
        5.3.2 Results
    5.4 Conclusion
Chapter 6 Mobi Cache: When k-anonymity Meets Cache
    6.1 Motivation
        6.1.1 Our Motivation
        6.1.2 Our Basic Idea
    6.2 Mobicache
        6.2.1 System Architecture
        6.2.2 Query to Neighbors
        6.2.3 Query to LBS Server
    6.3 Security Analysis
        6.3.1 Resistance to Colluding Attack
        6.3.2 Resistance to Inference Attack
    6.4 Performance
        6.4.1 Evaluation Setup
        6.4.2 Results
    6.5 Conclusion
Chapter 7 Priority-Aware Private Matching Schemes for PMSNs
    7.1 Motivation
    7.2 Our Basic Scheme
        7.2.1 Problem Statement
        7.2.2 Adversary Models and Privacy Goal
        7.2.3 Constructing Our Similarity Function
        7.2.4 P-match
    7.3 Our Proposed E-match
        7.3.1 Initialization
        7.3.2 E-match
        7.3.3 Discussions
        7.3.4 Case Study
    7.4 Security Analysis
        7.4.1 Analysis of the Basic Scheme
        7.4.2 Analysis of the E-match
    7.5 Performance Evaluations
        7.5.1 Complexity Analysis
        7.5.2 Experiment Setup
        7.5.3 Experiment Results
        7.5.4 Energy Consumption
    7.6 Conclusion
Chapter 8 Exactly Spatiotemporal Matching Scheme in Privacy-Aware MobileSocial Networks
    8.1 Motivation
    8.2 Our Solution
        8.2.1 Problem Statement
        8.2.2 Adversary Model
        8.2.3 System Architecture
        8.2.4 Initialization Phase
        8.2.5 Weight-Aware Pre-matching Module
        8.2.6 Reorganized Profile Exchanging Module
        8.2.7 Similarity Computing Module
    8.3 Security Analysis
        8.3.1 Security Proof of our Scheme Under the Malicious Adversary Model
        8.3.2 Security Proof of our Scheme Under the HBC Model
    8.4 Performance Evaluations
        8.4.1 Complexity Analysis
        8.4.2 Experiment Setup
        8.4.3 Experiment Results
        8.4.4 Energy Consumption
    8.5 Conclusion
Chapter 9 Conclusion and Future Work
Bibliography
致谢
作者简介



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