Chapter
2. Static and Dynamic Security Models
2.2 Stochastic Attack Graphs
2.4 Stochastic Petri Nets
3. Model-Based Analysis of System Security
3.1 Security Analysis Based on Classical Attack Graph Model
3.1.1 Reachability Analysis
3.1.2 Minimization Analysis
3.1.3 Model Checking Analysis
3.2 Security Analysis Based on the Stochastic Attack Graph Model
3.2.1 State Risk-Level Analysis
3.2.2 Stochastic Shortest Path Analysis
4. Security Analysis Based on Petri Nets
4.1 Security Analysis Based on Classical Petri Nets
4.1.1 Behavioral Analysis of Petri Nets
4.2 Security Analysis Based on Stochastic Petri Nets
Chapter Two: A Survey on Zero-Knowledge Proofs
1. Background and Motivation
2.1 Interactive Proof and Its Properties
2.3 Computational Indistinguishability
2.7 Witness Indistinguishability
2.8 Honest Verifier Versus General Cheating Verifier
2.9 Black-Box Simulator Versus Non-Black-Box Simulator
4.1 ZKP for Graph Three Colorability
4.2 ZKP for Feige–Fiat–Shamir Identification Scheme
4.4 ZKP for Hamiltonian Cycle
4.5 Another ZKP for Graph Three Colorability
4.7 ZKP for Circuit Computations
5. Advanced Topics in Composing ZKPs
5.1.1 The Richardson–Kilian Concurrent ZKP Protocol
5.1.2 The Improved Concurrent ZKP Protocol
5.2 Efficiency Considerations
5.4 Noninteractive Zero Knowledge
Chapter Three: Similarity of Private Keyword Search over Encrypted Document Collection
2. Background and Definitions
2.2 Searchable Encryption
2.2.1 Symmetric Searchable Encryption
2.2.2 Asymmetric Searchable Encryption
2.2.3 Security Requirements
2.3 Terminologies and Other Basic Tools
3. Constructing Similarity Keyword Set
3.1 Enumeration Technique
3.2 Wildcard-Based Technique
4. Constructing Secure Index
4.1 Inverted-Index-Based Secure Index
4.2 Symbol-Trie-Based Secure Index
4.3 LSH-Based Secure Index
4.4 Bed-Tree-Based Secure Index
4.5 Bilinear-Based Secure Index
5. Overview of Some Existing Schemes
5.2 Verifiable Symmetric-Key PKS
5.3 Verifiable Symmetric-Key PKS Using Twin Cloud
Chapter Four: Multiobjective Optimization for Software Refactoring and Evolution
1.2.1 Automating Defects Detection
1.2.2 Automating Defects Correction
2.1 Detection of Design Defects
2.1.2 Symptom-Based Detection
2.1.3 Metric-Based Approaches
2.1.4 Probabilistic Approaches
2.1.5 Machine Learning-Based Approaches
2.1.6 Visualization-Based Approaches
2.2 Correction of Design Defects
2.2.1 Manual and Semiautomated Approaches
2.2.2 Meta-Heuristic Search-Based Approaches
3.2.1 Step 1: Defects Detection
3.2.2 Step 2: Defects Correction
4. Design Defects Detection
4.1 Genetic Algorithm Overview
4.2 Genetic Algorithm Adaptation
4.2.1 Individual Representation
4.2.2 Generation of an Initial Population
4.2.3 Selection and Genetic Operators
4.2.4 Decoding of an Individual
4.2.5 Evaluation of an Individual
4.3.1 Goals and Objectives
4.3.3 Comparative Results
5. Design Defects Correction
5.2 Modeling the Refactoring Process as a Multiobjective Problem
5.2.3 Similarity with Recorded Code Changes
5.2.4 Semantic Preservation
5.3 NSGA-II for Software Refactoring
5.4.3 Algorithms Configuration
Contents of Volumes in This Series