This book presents the current state of the literature on the fields of homomorphic and searchable encryption, from both theoretical and practical points of view. Homomorphic and searchable encryption are still relatively novel and rapidly evolving areas and face practical constraints in the contexts of large-scale cloud computing and big data. Both encryption methods can be quantum-resistant if they use the right mathematical techniques. In fact, many fully homomorphic encryption schemes already use quantum-resistant techniques, such as lattices or characteristics of polynomials – which is what motivated the authors to present them in detail. On the one hand, the book highlights the characteristics of each type of encryption, including methods, security elements, security requirements, and the main types of attacks that can occur. On the other, it includes practical cases and addresses aspects like performance, limitations, etc. As cloud computing and big data already represent the future in terms of storing, managing, analyzing, and processing data, these processes need to be made as secure as possible, and homomorphic and searchable encryption hold huge potential to secure both the data involved and the processes through which it passes. This book is intended for graduates, professionals and researchers alike. Homomorphic and searchable encryption involve advanced mathematical techniques; accordingly, readers should have a basic background in number theory, abstract algebra, lattice theory, and polynomial algebra. Preface Contents Acronyms 1 Introduction 1.1 Motivation 1.2 Book Structure References 2 Background and Preliminaries 2.1 Mathematical Background and Notations 2.2 Cryptography Notations 2.3 Technologies 2.3.1 Cloud Computing and Big Data 2.3.2 Artificial Intelligence and Machine Learning 2.3.3 Internet of Things 2.3.4 Blockchain References 3 Homomorphic Encryption 3.1 History 3.2 Definitions 3.3 Types of Homomorphic Encryption Schemes 3.4 Fully Homomorphic Encryption 3.4.1 Classification 3.4.2 Standardization 3.4.3 Open Source Libraries 3.4.4 Implementations 3.5 Advancements in Homomorphic Encryption 3.5.1 Hardware Accelerators 3.5.2 Quantum Homomoprhic Encryption 3.5.3 Multi-party Computations 3.5.4 Zero-Knowledge Proof 3.6 Case Studies and Practical Applications 3.6.1 Cloud Computing and Big Data 3.6.2 Machine Learning and Artificial Intelligence 3.6.3 Blockchain 3.6.4 Internet of Things 3.7 Challenges and Research Directions References 4 Searchable Encryption 4.1 History 4.2 Components 4.2.1 Entities 4.2.2 Architecture 4.3 Security 4.3.1 Security Requirements 4.3.2 Security Models 4.4 Classification of Search Operations 4.4.1 Search Based on Keywords 4.4.2 Search Based on Regular Expressions 4.4.3 Semantic Search 4.5 Advancements in Searchable Encryption 4.5.1 Dynamic Searchable Encryption 4.5.2 Homomorphic Searchable Encryption 4.6 Case Studies and Applications 4.6.1 Cloud Computing and Big Data 4.6.2 Internet of Things 4.6.3 Blockchain 4.7 Challenges and Research Directions References Index Index
