隨著移動(dòng)設(shè)備及社交網(wǎng)絡(luò)技術(shù)的不斷發(fā)展,移動(dòng)社交網(wǎng)絡(luò)已經(jīng)變成一種在國內(nèi)、外移動(dòng)用戶之間快速增長的應(yīng)用。借助于智能手機(jī)、平板電腦等現(xiàn)代智能設(shè)備,移動(dòng)用戶可以通過訪問蘋果應(yīng)用商店或者谷歌應(yīng)用商店等下載諸多應(yīng)用軟件。通過各種不同的應(yīng)用軟件,從而1)享受各種服務(wù)運(yùn)營商所提供的服務(wù)信息,例如,基于位置服務(wù)信息;2)通過短距離通信技術(shù),如藍(lán)牙等實(shí)現(xiàn)與周圍用戶的相互通信,以共享彼此間的信息、視頻等,例如基于臨近度的移動(dòng)社交網(wǎng)絡(luò)。為了享受此類服務(wù),用戶通常需要泄漏其位置、興趣愛好或其他相關(guān)信息給不可信的第三方(例如基于位置服務(wù)中的服務(wù)器)或者周圍其他用戶作為第一步。然而由于此類服務(wù)器及周邊用戶往往可以獲取用戶的相關(guān)信息,包括用戶身處何時(shí)何地,希望獲取什么樣的請(qǐng)求,正在做什么等。擁有了這些信息,用戶可能被跟蹤,或者其信息被泄露給一些惡意第三方。因此,對(duì)用戶隱私的保護(hù)刻不容緩�，F(xiàn)有方案大都依賴可信第三方,或者難以為用戶提供滿足細(xì)粒度的隱私保護(hù)策略。本文提出了一系列解決方案,為移動(dòng)社交網(wǎng)絡(luò)用戶提供高效的隱私保護(hù),尤其是基于位置服務(wù)和基于用戶臨近度的移動(dòng)社交網(wǎng)絡(luò)。本文主要的貢獻(xiàn)如下:1)本章指出了背景信息在基于...

【文章頁數(shù)】：151 頁

【學(xué)位級(jí)別】：博士

【文章目錄】：
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
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