دانلود کتاب Automating Open Source Intelligence: Algorithms for OSINT

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Cover
Title Page
Copyright Page
Contents
List of Contributors
Chapter 1 - The Automating of Open Source Intelligence
The Commercial Angle
Algorithms
References
Chapter 2 - Named Entity Resolution in Social Media
Introduction
Evaluating Semantic Processing Performance
Characterizing Semantic Processing Errors
Meaning Loss in Biblical Proverbs: A Case Study
Models for Improving Semantic Processing Performance
Discussion
References
Chapter 3 - Relative Cyberattack Attribution
Introduction
Basic Attack Structure
Anonymization on the Internet
Weaknesses in Anonymization
Attribution as a Concept
Absolute Attribution
Relative Attribution
Relative attribution concepts
Inherent versus Learnt Behaviors
Hiding Behavior
Consistency of Behavior
Relative Attribution Techniques
Authorship Analysis
Limitations and Issues
Research Streams
Conclusions
References
Chapter 4 - Enhancing Privacy to Defeat Open Source Intelligence
Introduction
Scenario
Requirements and Threats
Preliminaries
The PIEMCP
Formal Security Analysis with CPN
Attack Scenarios
Verification Results
Removing Trusted ARM
Performance Analysis of FSSO-PIEMC
Comparison to Existing Approach
Conclusion and future work
References
Chapter 5 - Preventing Data Exfiltration: Corporate Patterns and Practices
What is Happening Around the World?
What is Happening in New Zealand?
Specifying the Problem
Problems Arising by Implementing Censorship
So, what should be done?
Summary
References
Chapter 6 - Gathering Intelligence on High-Risk Advertising and Film Piracy: A Study of the Digital Underground
Introduction
Advertising and risk
The digital millennium copyright act (DMCA)
Chilling Effects Database
Google Transparency Report
Mainstream advertising and how piracy is funded
High-Risk Advertising and their links to piracy websites
High-Risk Advertising: Case Studies in Canada
High-risk advertising: case studies in Australia
High-Risk Advertising: Case studies in New Zealand
Research Challenges
References
Chapter 7 - Graph Creation and Analysis for Linking Actors: Application to Social Data
Introduction
The Social Network Model
A Brief History of Graphs and Social Networks
Conceptual Framework
Graph Creation Techniques
Data Gathering
Defining and Computing Relationships
Disambiguation Techniques
Graph Analysis for OSINT
Structural Observations
Density of a Graph
Neighborhood, Degree, Average Degree, and Degree Distribution
Paths and Average Path Length
Components
Characterizing Position of Nodes
Betweenness Centrality
Closeness Centrality
Structures and Communities of Nodes
Structural Patterns: Cliques and Cores
Communities
Modularity
Twitter Case Study
The Twitter Dataset
General Graph Metrics
Node Metrics and Profiles’ Centrality
Communities
Conclusion
References
Chapter 8 - Ethical Considerations When Using Online Datasets for Research Purposes
Introduction
Existing Guidelines
Interpretation of Existing Guidelines for Online Purposes
The Three Proposed Principles Applied to Online Research
Autonomy
What Is Informed Consent in the Online Research?
When Is Informed Consent Required?
How Can Informed Consent Be Obtained and From Whom?
Obtaining Consent
Asking for Consent
Implied Consent
Culture
Other Ways of Implied Consent
How Can Provided Consent Be Validated?
Benefits Against Risks
Benefits
Risks
Harm to Participant
Harm for the Online Group
Harm for the Researcher
When Can These Risks Happen?
Justice
Summary
References
Chapter 9 - The Limitations of Automating OSINT: Understanding the Question, Not the Answer
Introduction
Finding Answers to Questions
Credibility and the Quality of Results
Relevance
The Limitations of Automating Osint
Conclusions
References
Chapter 10 - Geospatial Reasoning With Open Data
Introduction
The Open Geospatial Data Environment
Review of Reasoning Methods with Geospatial Data
Geospatial Domain Ontologies
Geospatial Service Ontologies
Qualitative Spatial Reasoning
Probabilistic Geospatial Reasoning
Fuzzy Geospatial Reasoning
Geospatial Reasoning With Multivalue Logics
Heuristic Geospatial Ontologies
Contextual Reasoning in the Geospatial Context
Standpoint Semantics for Geospatial Reasoning
Case Studies in Geospatial Reasoning
Case Study 1: Geospatial Reasoning for Map Buffering
Case Study 2: Nonclassical Geospatial Ontology Learning from Data
Case Study Data
Stage 1: Provisional Class Learning from Geometry Data
Stage 2: Class Learning from Geometry and Spatial Relations Data
Stage 3: Class Learning from Attribute Data
Assigning Probabilities to Instances
Results
Discussion
Conclusions
References
Subject Index
Back Cover