Xiangyun Tang – författare

Moving Target Defense (MTD) has been proposed as an innovative defense framework, which aims to introduce the dynamics, diversity and randomization into static network by the shuffling, heterogeneity and redundancy. It is born to solve the problem that traditional security solutions respond and defend against security threats after attacks occurrence, which will lead to the defender always having disadvantages in attack-defense confrontation. This book explores the challenges and solutions related to moving target defense in the cloud-edge-terminal networks.This book fills this gap by providing a comprehensive and detailed approach to designing intelligent MTD frameworks for cloud-edge-terminal networks. It is essential reading for researchers and professionals in network security and artificial intelligence who seek innovative defense solutions.The book is organized into 6 chapters, each addressing a key area of MTD and its integration with Artificial Intelligence. Chapter 1 introduces the fundamental concepts of MTD, security challenges in cloud-edge-terminal networks, and the role of artificial intelligence in enhancing MTD. Chapter 2 delves into host address mutation based on advantage actor-critic approach. Chapter 3 proposes a collaborative mutation-based MTD based on hierarchical reinforcement learning. Chapter 4 presents roadside units configuration mutation based on proximal policy optimization approach. Chapter 5 explores route mutation based on multiagent reinforcement learning. Chapter 6 provides a summary of insights and lessons learned throughout the book and outlines future research directions in MTD.

Moving Target Defense (MTD) has been proposed as an innovative defense framework, which aims to introduce the dynamics, diversity and randomization into static network by the shuffling, heterogeneity and redundancy. It is born to solve the problem that traditional security solutions respond and defend against security threats after attacks occurrence, which will lead to the defender always having disadvantages in attack-defense confrontation. This book explores the challenges and solutions related to moving target defense in the cloud-edge-terminal networks.This book fills this gap by providing a comprehensive and detailed approach to designing intelligent MTD frameworks for cloud-edge-terminal networks. It is essential reading for researchers and professionals in network security and artificial intelligence who seek innovative defense solutions.The book is organized into 6 chapters, each addressing a key area of MTD and its integration with Artificial Intelligence. Chapter 1 introduces the fundamental concepts of MTD, security challenges in cloud-edge-terminal networks, and the role of artificial intelligence in enhancing MTD. Chapter 2 delves into host address mutation based on advantage actor-critic approach. Chapter 3 proposes a collaborative mutation-based MTD based on hierarchical reinforcement learning. Chapter 4 presents roadside units configuration mutation based on proximal policy optimization approach. Chapter 5 explores route mutation based on multiagent reinforcement learning. Chapter 6 provides a summary of insights and lessons learned throughout the book and outlines future research directions in MTD.

Web 3.0 is the next generation of the Internet built on decentralized technologies such as blockchain and cryptography. It is designed to address issues encountered in the previous generation of the Internet such as imbalanced distribution of interests, monopoly of platform resources, and leakage of personal privacy. This book explores the challenges and solutions related to ensuring security and privacy in the context of the evolving Web 3.0 architecture.Web 3.0 represents the next generation of the web, characterized by decentralized networks, blockchain technology, and enhanced user control over data. As Web 3.0 evolves, the focus on addressing security and privacy concerns becomes increasingly crucial. This book provides a comprehensive understanding of the security and privacy issues specific to Web 3.0 and offers practical defense frameworks and methods to mitigate these challenges.This book is dedicated to the specific aspects of security and privacy in Web 3.0, from introducing the architecture and addressing the inherent issues to presenting innovative methods for privacy-preserving computing, user behavior identification, and abnormal transaction detection. It is of particular interest to researchers in the field of Web 3.0, blockchain, and network security, as it summarizes the security and privacy concerns in Web 3.0 and brings a number of innovative technologies and practical solutions to protect sensitive data and maintain user privacy in Web 3.0 environments, equipping researchers with the knowledge necessary to design secure and privacy-aware applications and systems in Web 3.0.