Part 1. Malware diffusion modeling framework
Chapter 1. Fundamentals of complex communications networks
1.1. Introduction to Communications Networks and Malicious Software
1.2. A Brief History of Communications Networks and Malicious Software
1.3. Complex Networks and Network Science
Chapter 2. Malware diffusion in wired and wireless complex networks
2.1. Diffusion Processes and Malware Diffusion
2.2. Types of Malware Outbreaks in Complex Networks
Chapter 3. Early malware diffusion modeling methodologies
Part 2. State-of-the-art malware modeling frameworks
Chapter 4. Queuing-based malware diffusion modeling
4.2. Malware Diffusion Behavior and Modeling via Queuing Techniques
4.3. Malware Diffusion Modeling in Nondynamic Networks
4.4. Malware Diffusion Modeling in Dynamic Networks with Churn
Chapter 5. Malware-propagative Markov random fields
5.3. Malware Diffusion Modeling Based on MRFs
5.5. Complex Networks with Stochastic Topologies
Chapter 6. Optimal control based techniques
6.2. Example—an Optimal Dynamic Attack: Seek and Destroy
Chapter 7. Game-theoretic techniques
7.3. Network-Malware Dynamic Game
Chapter 8. Qualitative comparison
8.2. Computational Complexity Comparison
8.3. Implementation Efficiency Comparison
Part 3. Applications and the road ahead
Chapter 9. Applications of state-of-the-art malware modeling frameworks
9.2. Dynamics of Information Dissemination
9.3. Malicious-information Propagation Modeling
10.2. Open Problems for Queuing-based Approaches
10.3. Open Problems for MRF-based Approaches
10.4. Optimal Control and Dynamic Game Frameworks
10.5. Open Problems for Applications of Malware Diffusion Modeling Frameworks
Appendix A. Systems of ordinary differential equations
A.2. First-order Differential Equations
A.3. Existence and Uniqueness of a Solution
A.4. Linear Ordinary Differential Equations
Appendix B. Elements of queuing theory and queuing networks
B.2. Basic Queuing Systems, Notation, and Little’s Law
B.3. Markovian Systems in Equilibrium
Appendix C. Optimal control theory and Hamiltonians
C.1. Basic Definitions, State Equation Representations, and Basic Types of Optimal Control Problems
C.3. Finding Trajectories that Minimize Performance Measures
C.4. Variational Approach for Optimal Control Problems
C.5. Numerical Determination of Optimal Trajectories
C.6. Relationship Between Dynamic Programming (DP) and Minimum Principle
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