
Big Data and Cloud: Trust, Security and Privacy
Beschreibung
Weitere Details
Weitere Ausgaben
Inhalt
- Intro
- Contents
- Preface
- Chapter 1
- Big Data: An Introduction
- Introduction
- Big Data: Dimensions and Sources
- Big Data Sources
- Big Data: Issues and Challenges
- The Volume Problem
- The Velocity Challenge
- The Variety Problem
- The Value Problem
- The Veracity problem
- Big Data Opportunities
- Technologies for Big Data Solutions
- Ensuring Big Data Maturity
- Conclusion
- References
- Chapter 2
- Big Data and Cloud Computing
- Introduction
- Why Use the Cloud?
- Cloud Computing and Business
- Cloud Computing and Health Care
- Cloud Operating Systems
- Big Data in the Cloud
- Cloud Security in Big Data
- Big Data Programming in the Cloud
- MapReduce
- MapReduce Principles
- Hadoop MapReduce
- Factors Affecting Hadoop/MapReduce
- Conclusion
- References
- Chapter 3
- Big Data Management Analysis
- Introduction
- Algorithms and Systems for Big Data Search
- Distributed and Peer-to-Peer Search
- Big Data Search Architectures, Scalability, and Efficiency
- Data Acquisition, Integration, Cleaning, and Best Practices
- Visualization Analysis for Big Data
- Computational Modeling and Data Integration
- Large-scale Recommendation Systems and Social Media Systems
- Background Story
- Functioning
- Standards
- Security Implications
- Future Trends
- Cloud/Grid/ Stream Data Mining - Big Velocity Data
- Link and Graph Mining
- Semantic-based Data Mining and Data Processing
- Mobility and Big Data
- Multimedia and Multi-Structured Data - Big Variety Data
- Conclusion and Further Works
- References
- Chapter 4
- Diversity in Big Data Applications
- Abstract
- Introduction
- Big Data as a Service
- Big Data Analytics
- Big Data Analytics Standards
- Streaming
- Storage Engine Interfaces
- Querying
- Benchmarks
- Security and Governance
- Metadata Management
- Deployment
- Integration with Other Emerging Technologies
- Big Data Analytics Applications
- Healthcare
- Public Sector
- Learning Institutions
- Industrial and Natural Resources
- Transportation
- Finance
- Small Business Enterprises (SMEs)
- Conclusion
- References
- Chapter 5
- Big Data Security Challenges and Management
- Introduction
- Definitions and Characteristics of Big Data
- Why Big Data Security Issues Are Surfacing
- Security and Privacy Approaches
- Big Data Analytics For Security
- Protecting Transaction Logs and Data
- How the Transaction Logs Work in Data Management?
- Maintaining Transaction Log
- Validation and Filtration and End-Point Inputs
- Securing and Protecting Data in Real Time
- Data Provenance
- Securing Distributed Framework Calculations and Other Processes
- Granular Access Control
- Privacy Protection for Non-Rational Data Stores
- Big Data Security Challenges
- The Suggested Framework for Big Data Infrastructure Security Components
- Big Data Security Lifecycle
- Data Collection Phase
- Data Storage Phase
- Data Analysis Phase
- Knowledge Synthesis Phase
- Data-centric Access Control
- XACML Policies for Fine Granular Access Control
- Access Control in NoSQL Databases
- Encryption Enforced Access Control
- Trusted Environment
- Trusted Infrastructure Bootstrapping Protocol
- The Domain Authentication Server (DAS)
- The Bootstrap Initiator (BI)
- Bootstrap Requester (BREQ)
- Bootstrap Responder (BRES)
- FADI for Cooperation and Services Integration
- Conclusion
- References
- Chapter 6
- Big Data Transformation into Big Values
- Introduction
- Big Data Classification
- Market Adoption
- How Does Making Big Data Accessible to Your Team Drive Value?
- Ways of Making Big Data Have Big Value
- Choose the Right Method for Accessing Big Data
- Getting Insights Is as Much about Relating Data as It Is Collecting It
- Give Your Entire Organization Access to Big Data
- Make It Easy For Users to Find the Data They Need
- Drive Collaboration to Drive Innovation
- Use an Agile Analytics Environment That Can Meet the Needs of Every User
- Provide Access to Analytics Solutions Anywhere, on Any Device
- Implement a Scalable Solution that Grows with Your Organization's Changing Needs
- Ensure Your Business Intelligence Solution Can Easily Adapt to Future Technologies
- Choose a Business Intelligence Solution with an Extensive Partner Ecosystem
- Conclusion
- References
- Chapter 7
- Role of Big Data Analytic on IoT
- Abstract
- Introduction
- Big Data
- Data Compliance (Social Value)
- Data's Product Development Value
- The Value of Dark Data
- Case 1
- Big Data and Predictive Analysis
- The Internet of Things
- Impact of the Internet of Things on Businesses
- Advantages of Internet of Things to Businesses
- Disadvantages of the Internet of Things to Businesses
- The Response of Big 4 Auditing Companies to the Internet of Things
- Big Data Analytics
- Predictive Analytics
- Prescriptive Analytics
- Descriptive Analytics
- The Relationship between Big Data and IoT
- Big Data Analytics Methods
- Classification
- Clustering
- Association
- Prediction
- The Architecture of IoT Including Big Data Analytics
- Challenges and Further Research Topics
- Privacy
- Data Mining
- Visualization
- Integration
- Conclusion
- References
- Chapter 8
- The Convergence of Big Data, the Internet of Things and Cloud Computing
- Introduction
- Big Data
- Internet of Things (IoT)
- Cloud Computing
- A Relationship between Big Data, Cloud and the Internet of Things
- Convergence of Big Data, Cloud Computing and the Internet of Things
- Big Data and Cloud
- Big Data, Data Science, and Cloud
- Benefits of Convergence of Big Data, Internet of Things and Cloud Computing
- Technology Challenges as a Result of the Convergence
- Issues in Big Data and Internet of Things
- Issues in Cloud
- Technological Issues Unsolved after Convergence of the Three Technologies
- Conclusion
- References
- Chapter 9
- Cloud Structures and Industrial IoT
- Introduction
- History of Cloud Computing
- The Present State of Cloud Computing
- Cloud Computing in the Entertainment
- Cloud Computing and Business
- The Future of Cloud Computing
- Significant Trends
- Growth of the Hybrid Cloud Adoption
- User Are Leveraging 6 Cloud on Average
- Common Example of Cloud Computing
- Hardware That Support the Cloud Computing
- Impact of Cloud computing
- Social Impact
- Education
- Development
- Health
- Organizational Impact of Cloud Computing
- Challenges That Are Facing the Adoption of Cloud Computing
- Challenges in the Adoption of Cloud Computing
- Misalignment and Conflict of Goals
- Recommendations
- Cloud, IoT and Big Data
- Cloud Service Models
- Internet of Things (IoT)
- Industrial IoT (IIoT)
- References
- Chapter 10
- The Security Challnges of Big Data
- Introduction
- Forms of Big Data
- Structured Data
- Unstructured Data
- Semi-Structured Data
- Features of Big Data
- Benefits of Big Data Processing
- Decision Making
- Efficacy in Operation
- Challenges of Big Data
- Single Layer Protection
- NOSQL
- Transactional Integrity
- Authentication Method
- Data Transfers
- Validation
- Unethical Manpower
- Access Control Encryption
- Audits
- Monitoring and Tracking
- Organization
- The Security Problems of Big Data
- The Problem of False or Fake Data Generation
- Possibility of the Presence of Mappers Who Are Not Trusted
- Cryptographic Protection
- Mining of Sensitive Information
- Granular Access Control Struggles
- Difficulties in Data Provenance
- Absence of Security Audit
- Solutions for Big Data Security
- The Loss to Organizations on Big Data Piracy
- The Data Become Unorganized and Unable to Be Used
- Storage of Data Is a Concern
- The Cost of Losing Revenue Is Great
- The Loss of Privacy in the Information
- Fundamental Steps in Strong Big Data Security
- Step 1: Get Security Measures from the Starting Itself
- Step 2: Start With Objectives Rather Than Solutions
- Step 3: Customize the Solution
- Conclusion
- References
- Chapter 11
- Big Data Analytics: IoT and Privacy Challenges
- Introduction
- Data Processing
- Challenges
- Time
- Incompleteness and Context Awareness
- Scalability and Performance
- Text Analytics
- Web Analytics
- Mobile Analytics
- Strength
- Weakness
- Opportunities
- Internet of Things (IoT)
- Delay Tolerance and Asynchrony
- Security in IoT for Both Consumer and Producer
- Privacy in IoT
- Self-Service Analytics
- IoT and Big Data Analytics
- Existing Analytics Systems
- Relationship between IoT and Big Data Analytics
- Privacy Challenges of Big Data in IoT Era
- Stakeholder Responsibility
- Conclusion
- References
- Chapter 12
- Big Data: Security, Privacy and Trust
- Introduction
- Intrusion Detection for Gigabit Networks
- Anomaly and APT Detection in Very Large Scale Systems
- High-Performance Cryptography
- Visualizing Large Scale Security Data
- Threat Detection Using Big Data Analytics
- Privacy Threats of Big Data
- Big Data Collection/Analysis: Privacy-Preserving
- HCI Challenges for Big Data Security and Privacy
- User Study for Threat detection in Big data
- Sociological Aspects of Big Data Privacy
- Trust Management in IoT and Other Big Data Systems
- Conclusion
- References
- About the Authors
- Index
- Blank Page
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