Security, Privacy and Reliability in Computer Communications and Networks.

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sha, Kewei
Otros Autores: Striegel, Aaron, Song, Min
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Aalborg : River Publishers, 2016.
Colección:River Publishers series in communications.
Temas:
Computer networks > Security measures.
Réseaux d'ordinateurs > Sécurité > Mesures.
Computer networks > Security measures
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • Half Title Page
  • RIVER PUBLISHERS SERIES IN INNOVATION AND CHANGE IN EDUCATION
  • CROSS-CULTURAL PERSPECTIVE
  • Title Page
  • Security, Privacy and Reliability in Computer Communications and Networks
  • Copyright Page
  • Contents
  • Preface
  • Acknowledgments
  • List of Contributors
  • List of Figures
  • List of Tables
  • List of Algorithms
  • List of Abbreviations
  • PART I
  • Privacy
  • Chapter 1
  • Distributed Beamforming Relay Selection to Increase Base Station Anonymity in Wireless Ad Hoc Networks
  • Abstract
  • 1.1 Introduction
  • 1.2 Anonymity Definition, Metrics, and Contemporary Measures
  • 1.2.1 Anonymity Definition and Assessment
  • 1.2.2 Antitraffic Analysis Measures
  • 1.3 System Assumptions and Attack Model
  • 1.3.1 Network Model
  • 1.3.2 Adversary Model
  • 1.3.3 Evidence Theory and Belief Metric
  • 1.4 Distributed Beamforming to Increase the BS Anonymity
  • 1.4.1 Overview of the DiBAN Protocol
  • 1.4.2 DiBAN Illustrative Example
  • 1.4.3 DiBAN Energy Analysis
  • 1.5 Distributed Beamforming Relay Selection Approach
  • 1.6 Validation Experiments
  • 1.6.1 Simulation Environment
  • 1.6.2 Simulation Results
  • 1.7 Conclusions and FutureWork
  • Appendix I: Numerical Evidence Theory Belief Calculation Example
  • References
  • Chapter 2
  • A Privacy-Preserving and Efficient Information Sharing Scheme for VANET Secure Communication
  • Abstract
  • 2.1 Introduction
  • 2.2 Related Works
  • 2.3 System Model and Preliminaries
  • 2.3.1 Network Model
  • 2.3.2 Attack Model
  • 2.3.3 Security Requirements
  • 2.4 The Proposed PETS Scheme
  • 2.4.1 Scheme Overview
  • 2.4.2 System Initiation
  • 2.4.3 Vehicle-RSU Key Agreement
  • 2.4.4 Traffic Information Collection and Aggregation
  • 2.4.5 Traffic Jam Message Propagation
  • 2.5 Security Analysis
  • 2.6 Performance Evaluation
  • 2.6.1 Traffic Information Sending/Collection Overhead.
  • 2.6.2 Traffic Information Propagation/Verification Overhead
  • 2.6.3 Scheme Simulation
  • 2.7 Conclusion
  • References
  • PART II
  • Vulnerabilities, Detection and Monitoring
  • Chapter 3
  • DIAMoND: Distributed Intrusion/Anomaly Monitoring for Nonparametric Detection
  • Abstract
  • 3.1 Introduction
  • 3.2 Literature Review
  • 3.3 System Design
  • 3.3.1 Architecture Overview
  • 3.3.2 Detection Unit
  • 3.3.3 Coordination Unit
  • 3.3.4 Communication Protocol
  • 3.3.5 Neighborhood Strategies
  • 3.3.6 Rogue Nodes
  • 3.4 Evaluation Setup
  • 3.4.1 Software Implementation
  • 3.4.2 Physical Topologies
  • 3.4.3 Legitimate and Malicious Traffic
  • 3.5 Emulation Results
  • 3.5.1 Detection Accuracy
  • 3.5.2 Impact of Physical Topologies
  • 3.5.3 Influence of Neighborhood Strategies
  • 3.5.4 Minimal and Marginal Deployment Gain
  • 3.6 Conclusions
  • Acknowledgments
  • References
  • Chapter 4
  • Detection of Service Level Agreement (SLA) Violations in Memory Management in Virtual Machines
  • Abstract
  • 4.1 Introduction
  • 4.2 Related Work
  • 4.2.1 Information Leakage among Virtual Machines
  • 4.2.2 Service Level Agreement Enforcement
  • 4.3 The Proposed Approaches
  • 4.3.1 Memory Overcommitment in Virtualization Environments
  • 4.3.2 Memory Deduplication in VM Hypervisors
  • 4.3.3 System Assumptions
  • 4.3.4 Basic Ideas of the Proposed Approaches
  • 4.3.5 Details of Implementation
  • 4.3.5.1 Choice of memory pages
  • 4.3.5.2 Measurement of access time
  • 4.3.5.3 Verification of memory access order
  • 4.3.6 Detection Procedures of the SLA Violations
  • 4.4 Experimental Results
  • 4.4.1 Experimental Environment Setup
  • 4.4.2 Experiments and Results
  • 4.4.3 Impacts on System Performance
  • 4.5 Discussion
  • 4.5.1 Reducing False Alarms
  • 4.5.2 Impacts of Extra Memory Demand
  • 4.5.3 Building A Unified Detection Algorithm
  • 4.6 Conclusion
  • References.
  • Chapter 5
  • Analysis of Mobile Threats and Security Vulnerabilities for Mobile Platforms and Devices
  • Abstract
  • 5.1 Introduction
  • 5.2 Analysis of Mobile Platforms
  • 5.2.1 Dominating Mobile Platforms
  • 5.2.1.1 iPhone Operating System (iOS)
  • 5.2.1.2 Android operating system (Android)
  • 5.2.1.3 BlackBerry operating system
  • 5.2.2 Security Models for Mobile Platforms
  • 5.2.2.1 iOS security model
  • 5.2.2.2 Android security model
  • 5.2.2.3 BlackBerry security model
  • 5.2.3 Existing Security Vulnerabilities in Mobile Platforms
  • 5.2.3.1 Potential vulnerabilities
  • 5.2.3.2 Mobile device malware
  • 5.3 Threat Model for Mobile Platforms
  • 5.3.1 Goals and Motives for an Attacker
  • 5.3.1.1 Cybercriminals: outsourcing sensitive data
  • 5.3.1.2 Cybercriminals: cyber heist
  • 5.3.1.3 Cybercriminals: corporate espionage and sabotage
  • 5.3.2 Attack Vectors or Modern Exploitation Techniquesfor Mobile Devices
  • 5.3.2.1 Susceptibility on the mobile through hardware
  • 5.3.2.2 Attacking through the Web
  • 5.3.2.3 Mobile intrusion and deception through social engineering
  • 5.3.2.4 Attacking through the mobile network
  • 5.3.2.5 Cyber Arson through common mobile applications
  • 5.3.2.6 Attacking via Bluetooth connection
  • 5.3.3 Types of Malwares in Mobile Devices
  • 5.3.3.1 Trojan-related malware
  • 5.3.3.2 Worms targeting mobile devices
  • 5.3.3.3 Viruses on the mobile
  • 5.3.3.4 Ransomware: a mobile kidnapping
  • 5.3.3.5 Mobile botnets
  • 5.4 Defense Mechanisms for Securing Mobile Platforms
  • 5.4.1 Keychain Authentication and Encryption
  • 5.4.2 Binary Protection and Hardening
  • 5.4.3 Third-Party OS Products
  • 5.4.4 Obfuscators and Optimizers
  • 5.4.5 Compiler and Linker Defense Mechanisms
  • 5.4.6 Certificate-based Mobile Authentication
  • 5.4.7 Token-based Mobile Authentication
  • 5.4.8 Summary
  • 5.5 Related Work.
  • 5.6 Threats Analysis and Future Trends
  • 5.7 Conclusion
  • References
  • PART III
  • Cryptographic Algorithms
  • Chapter 6
  • Quasigroup-Based Encryption for Low-Powered Devices
  • Abstract
  • 6.1 Introduction
  • 6.2 Background-Low Energy Cryptosystems
  • 6.3 Overview of Quasigroup Encryption
  • 6.4 The Preliminary Block Cipher Design
  • 6.5 Overview of Software Implementation
  • 6.6 Overview of Three FPGA Implementations
  • 6.6.1 The Quasigroup Implementation
  • 6.6.2 Comparison Design-Parallel AES
  • 6.6.3 Hybrid Front-End/AES Design
  • 6.7 Experimental Results
  • 6.8 Toward a Single-Chip Implementation
  • 6.9 Algorithm Results for B = 2 to 8
  • 6.10 Generating Quasigroups Fast
  • 6.11 Our Quasigroup Block Cipher Algorithm
  • 6.12 Cryptanalysis and Improvements in the Block Cipher
  • 6.13 Overview of a General Linear Cryptanalytical Attack
  • 6.14 The LAT Design
  • 6.15 Pilingup Attempts for N = 16, 32, and 64
  • 6.16 Analysis of the Attack on the Quasigroup
  • 6.17 The Issue of a Total Linear Bias of 1/2
  • 6.18 Attack Complexity
  • 6.19 Possible Changes that Could Be Made in the Design of This Attack Model
  • 6.20 Which Quasigroup Order Is Best?
  • 6.21 Conclusions
  • References
  • Chapter 7
  • Measuring Interpretation and Evaluationof Client-side Encryption Tools in Cloud Computing
  • Abstract
  • 7.1 Introduction
  • 7.2 Cloud Service Providers (CSPs)
  • 7.3 Deployment Model of Cloud Service Provider
  • 7.4 Methodology
  • 7.5 Deriving the Attributes of Existing Tools
  • 7.5.1 AxCrypt
  • 7.5.2 nCrypted Cloud
  • 7.5.3 SafeBox
  • 7.5.4 SpiderOak
  • 7.5.5 Viivo
  • 7.6 Comparison of the Studied Tools
  • 7.7 Characteristics of the Studied Tools
  • 7.8 Security of Encryption and Key Generation Mechanisms of the Studied Tools
  • 7.9 Performance Measurement and Analysis
  • 7.9.1 System Setup
  • 7.9.1.1 Application tools
  • 7.9.1.2 Cloud service provider.
  • 7.9.1.3 Testing environment
  • 7.9.2 Analysis
  • 7.10 Results and Discussion
  • 7.11 Conclusion and Future Work
  • References
  • Chapter 8
  • Kolmogorov-Smirnov Test-based Side-channel Distinguishers: Constructions, Analysis, and Implementations
  • 8.1 Introduction
  • 8.2 Preliminaries
  • 8.2.1 Kolmogorov-Smirnov Test
  • 8.2.2 KSA Distinguisher
  • 8.2.3 PKS Distinguisher
  • 8.3 Systematic Construction of KS Test-based Side-channel Distinguishers
  • 8.3.1 Construction Strategies of KSA and PKS
  • 8.3.2 Nine Variants of KS Test-based Distinguishers
  • 8.4 An Experiment Analysis of All Twelve KS Test-based Side-channel Distinguishers
  • 8.5 Implementation Methods of MPC-KSA [13]
  • 8.5.1 Analysis of the Naive Method
  • 8.5.2 Optimized Method I
  • 8.5.3 Optimized Method II
  • 8.6 Implementation Results
  • 8.7 Conclusions
  • Acknowledgments
  • References
  • Chapter 9
  • Multi-antenna Transmission Technique with Constellation Shaping for Secrecy at Physical Layer
  • Abstract
  • 9.1 Introduction
  • 9.2 Transmitter Structure
  • 9.3 Transmitter Configuration Possibilities and Security
  • 9.4 Receivers and the Impact of Information Directivity
  • 9.4.1 Simulation Results
  • 9.4.2 Transmitter Configuration Effects in MI and Secrecy
  • 9.5 Conclusions
  • Acknowledgments
  • References
  • PART VI
  • Reliable System Design
  • Chapter 10 -Active Sub-Areas-Based Multi-Copy Routing in VDTNs
  • Abstract
  • 10.1 Introduction
  • 10.2 RelatedWork
  • 10.3 Identification of Each Vehicle's Active Sub-areas
  • 10.4 Trace Measurement
  • 10.4.1 Vehicle Mobility Pattern
  • 10.4.2 Relationship between Contact and Location
  • 10.5 Active Area-based Routing Method
  • 10.5.1 Traffic-Considered Shortest Path Spreading
  • 10.5.1.1 Road traffic measurement
  • 10.5.1.2 Building traffic-considered shortest path tree
  • 10.5.2 Contact-based Scanning in Each Active Sub-area.

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