Advances in Computers ( Volume 94 )

Publication series :Volume 94

Author: Hurson   Ali R.  

Publisher: Elsevier Science‎

Publication year: 2014

E-ISBN: 9780128003251

P-ISBN(Paperback): 9780128001615

P-ISBN(Hardback):  9780128001615

Subject: TP274 数据处理、数据处理系统

Language: ENG

Access to resources Favorite

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Description

Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in computer hardware, software, theory, design, and applications. It has also provided contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

  • In-depth surveys and tutorials on new computer technology
  • Well-known authors and researchers in the field
  • Extensive bibliographies with most chapters
  • Many of the volumes are devoted to single themes or subfields of computer science

Chapter

1. Introduction

2. Static and Dynamic Security Models

2.1 Attack Graphs

2.2 Stochastic Attack Graphs

2.3 Petri Nets

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

3.1.4 Attribute 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

5. Conclusions

Chapter Two: A Survey on Zero-Knowledge Proofs

1. Background and Motivation

2. Introduction

2.1 Interactive Proof and Its Properties

2.2 A Simple Example

2.3 Computational Indistinguishability

2.4 One-Way Function

2.5 Simulation Paradigm

2.6 Definition of ZKP

2.7 Witness Indistinguishability

2.8 Honest Verifier Versus General Cheating Verifier

2.9 Black-Box Simulator Versus Non-Black-Box Simulator

2.10 Quality of ZKPs

3. NP Problem and ZKPs

4. ZKP Applications

4.1 ZKP for Graph Three Colorability

4.2 ZKP for Feige–Fiat–Shamir Identification Scheme

4.3 ZKP for GI

4.4 ZKP for Hamiltonian Cycle

4.5 Another ZKP for Graph Three Colorability

4.6 ZKP Sketch for SAT

4.7 ZKP for Circuit Computations

4.8 ZKP for Exact Cover

4.9 ZKP for 0–1 Knapsack

5. Advanced Topics in Composing ZKPs

5.1 Composing ZKPs

5.1.1 The Richardson–Kilian Concurrent ZKP Protocol

5.1.2 The Improved Concurrent ZKP Protocol

5.2 Efficiency Considerations

5.3 Knowledge Complexity

5.4 Noninteractive Zero Knowledge

6. Conclusion

References

Chapter Three: Similarity of Private Keyword Search over Encrypted Document Collection

1. Introduction

2. Background and Definitions

2.1 Similarity Metric

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

5.1 Symmetric-Key PKS

5.2 Verifiable Symmetric-Key PKS

5.3 Verifiable Symmetric-Key PKS Using Twin Cloud

5.4 LSH-Based PKS

5.5 Bed-Tree Multi-PKS

5.6 Public-Key PKS

5.7 Classification

6. Conclusion

Chapter Four: Multiobjective Optimization for Software Refactoring and Evolution

1. Introduction

1.1 Research Context

1.2 Problem Statement

1.2.1 Automating Defects Detection

1.2.2 Automating Defects Correction

1.3 Proposed Solutions

2. Related Work

2.1 Detection of Design Defects

2.1.1 Manual Approaches

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. Proposal

3.1 Research Objective

3.2 Methodology

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 Validation

4.3.1 Goals and Objectives

4.3.2 Systems Studied

4.3.3 Comparative Results

4.3.4 Discussion

5. Design Defects Correction

5.1 Approach Overview

5.2 Modeling the Refactoring Process as a Multiobjective Problem

5.2.1 Quality

5.2.2 Code Changes

5.2.3 Similarity with Recorded Code Changes

5.2.4 Semantic Preservation

5.3 NSGA-II for Software Refactoring

5.3.1 NSGA-II Overview

5.3.2 NSGA-II Adaptation

5.4 Validation

5.4.1 Research Questions

5.4.2 Setup

5.4.3 Algorithms Configuration

5.4.4 Results

5.4.5 Discussion

6. Conclusion

Author Index

Subject Index

Contents of Volumes in This Series

The users who browse this book also browse