Artificial Intelligence and Data Mining Approaches in Security Frameworks. Группа авторов
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Table of Contents
1 Cover
4 Preface
5 1 Role of AI in Cyber Security 1.1 Introduction 1.2 Need for Artificial Intelligence 1.3 Artificial Intelligence in Cyber Security 1.4 Related Work 1.5 Proposed Work 1.6 Conclusion References
6 2 Privacy Preserving Using Data Mining 2.1 Introduction 2.2 Data Mining Techniques and Their Role in Classification and Detection 2.3 Clustering 2.4 Privacy Preserving Data Mining (PPDM) 2.5 Intrusion Detection Systems (IDS) 2.6 Phishing Website Classification 2.7 Attacks by Mitigating Code Injection 2.8 Conclusion References
7 3 Role of Artificial Intelligence in Cyber Security and Security Framework 3.1 Introduction 3.2 AI for Cyber Security 3.3 Uses of Artificial Intelligence in Cyber Security 3.4 The Role of AI in Cyber Security 3.5 AI Impacts on Cyber Security 3.6 The Positive Uses of AI Based for Cyber Security 3.7 Drawbacks and Restrictions of Using Computerized Reasoning For Digital Security 3.8 Solutions to Artificial Intelligence Confinements 3.9 Security Threats of Artificial Intelligence 3.10 Expanding Cyber Security Threats with Artificial Consciousness 3.11 Artificial Intelligence in Cybersecurity – Current Use-Cases and Capabilities 3.12 How to Improve Cyber Security for Artificial Intelligence 3.13 Conclusion References
8 4 Botnet Detection Using Artificial Intelligence 4.1 Introduction to Botnet 4.2 Botnet Detection 4.3 Botnet Architecture 4.4 Detection of Botnet 4.5 Machine Learning 4.6 A Machine Learning Approach of Botnet Detection 4.7 Methods of Machine Learning Used in Botnet Exposure 4.8 Problems with Existing Botnet Detection Systems 4.9 Extensive Botnet Detection System (EBDS) 4.10 Conclusion References
9 5 Spam Filtering Using AI 5.1 Introduction 5.2 Content-Based Spam Filtering Techniques 5.3 Machine Learning–Based Filtering 5.4 Performance Analysis 5.5 Conclusion References
10 6 Artificial Intelligence in the Cyber Security Environment 6.1 Introduction 6.2 Digital Protection and Security Correspondences Arrangements 6.3 Black Tracking 6.4 Spark Cognition Deep Military 6.5 The Process of Detecting Threats 6.6 Vectra Cognito Networks 6.7 Conclusion References
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7 Privacy in Multi-Tenancy Frameworks Using AI
7.1 Introduction
7.2 Framework of Multi-Tenancy
7.3 Privacy and Security in Multi-Tenant Base System Using AI