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Artificial Intelligence for Security Enhancing Protection in a Changing World /

This book discusses the use of artificial intelligence (AI) for security purposes. It is divided into three parts: methodological fundamentals of AI, use of AI for critical infrastructure protection and anomaly detection. The first section describes the latest knowledge for creating safe AIs and usi...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Sipola, Tuomo (Editor), Alatalo, Janne (Editor), Wolfmayr, Monika (Editor), Kokkonen, Tero (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edition:1st ed. 2024.
Subjects:
Data protection > Law and legislation.
Artificial intelligence.
Computer networks > Security measures.
Privacy.
Artificial Intelligence.
Mobile and Network Security.
Online Access:https://doi.org/10.1007/978-3-031-57452-8
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Table of Contents:
  • Part I Methodological Fundamentals of Artificial Intelligence
  • Chapter.1.Safeguarding the Future of Artificial Intelligence: An AI Blueprint
  • Chapter.2.Cybersecurity and the AI Silver Bullet.-Chapter.3.Artificial Intelligence and Differential Privacy – Review of Protection Estimate Models
  • Chapter.4.To Know What You Do Not Know: Challenges for Explainable AI for Security and Threat Intelligence
  • Chapter.5.Securing the Future: The Role of Knowledge Discovery Frameworks
  • Chapter.6.Who Guards the Guardians? On Robustness of Deep Neural Networks.-Part II Artificial Intelligence for Critical Infrastructure Protection
  • Chapter.7.Opportunities and Challenges of Using Artificial Intelligence in Securing Cyber-Physical System
  • Chapter.8.Artificial Intelligence Working to Secure Small Enterprises
  • Chapter.9.On the Cyber Security of Logistics in the Age of Artificial Intelligence.-Chapter.10.Fuzzy Machine Learning for Smart Grid Instability Detection
  • Chapter.11.On Protection of the Next-Generation Mobile Networks against Adversarial Examples
  • Chapter.12.Designing and Implementing an Interactive Cloud Platform for Teaching Machine Learning with Medical Data
  • Part III Artificial Intelligence for Anomaly Detection
  • Chapter.13.Machine Learning and Anomaly Detection for an Automated Monitoring of Log Data
  • Chapter.14.Detecting Web Application DAST Attacks in Large-scale Event.-Chapter15.Enhancing IoT Intrusion Detection Using Hybrid DAIDS-RNN Mode.

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