Artificial Intelligence Techniques for Analysing Sensitive Data in Medical Cyber-Physical Systems: System Protection and Data Analysis

Ficco, Massimo, D'Angelo, Gianni

  • 出版商: Springer
  • 出版日期: 2025-01-06
  • 售價: $6,950
  • 貴賓價: 9.5$6,603
  • 語言: 英文
  • 頁數: 168
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031707745
  • ISBN-13: 9783031707742
  • 相關分類: 人工智慧Data Science
  • 尚未上市,無法訂購

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商品描述

This book presents the major advances in techniques to preserve privacy and security requirements connected with the use of AI and machine learning (ML) to analyse and manage sensitive data in MCPSs. The advances in Internet of things and artificial intelligence (AI) have witnessed great progress on healthcare technologies in several application domains. In particular, the interconnection between the physical spaces, characterized by physical devices able to collect users' health information, with the cyberspace, also known as the virtual space, has fostered the development of intelligent Medical Cyber-Physical Systems (MCPSs) with the capability to deliver real-time healthcare services. On the other hand, the potential innovation that these technologies bring to improve patient care, by remotely analysing health parameters using medical devices, advanced smart sensors, and AI, is hampered by security and privacy challenges related to the managed sensitive data.

Starting from the state of the art on AI and ML for medical applications and digital health, an accurate analysis of privacy and security risks associated with the use of the MCPSs is presented. Then, Digital Twins are introduced as a significant technique to enhance decision-making through learning and reasoning of collected on-field real-time data. Moreover, decentralized healthcare data management approaches based on federated learning, tiny machine learning, and blockchain technologies have been introduced to shift control and responsibility of healthcare data management from individual centralized entities to a more distributed structure, preserving privacy and security. Finally, the application of AI-based security monitoring approaches in healthcare is discussed.

In this book, both theoretical and practical approaches are used to allow readers to understand complex topics and concepts easily also through real-life scenarios.

商品描述(中文翻譯)

本書介紹了在使用人工智慧(AI)和機器學習(ML)分析和管理敏感數據的醫療網路物理系統(MCPSs)中,與隱私和安全要求相關的主要技術進展。物聯網和人工智慧的進步在多個應用領域的醫療技術上取得了顯著進展。特別是,物理空間與網路空間(也稱為虛擬空間)之間的互聯,透過能夠收集用戶健康資訊的物理設備,促進了智能醫療網路物理系統(MCPSs)的發展,這些系統具備提供即時醫療服務的能力。另一方面,這些技術在改善病人護理方面的潛在創新,透過使用醫療設備、高級智能感測器和AI遠程分析健康參數,卻受到與管理的敏感數據相關的安全和隱私挑戰的阻礙。

本書從醫療應用和數位健康的AI與ML的最新技術開始,準確分析了與使用MCPSs相關的隱私和安全風險。接著,介紹了數位雙胞胎作為一項重要技術,透過學習和推理收集的現場即時數據來增強決策制定。此外,基於聯邦學習、微型機器學習和區塊鏈技術的去中心化醫療數據管理方法被引入,以將醫療數據管理的控制和責任從個別集中實體轉移到更分散的結構,從而保護隱私和安全。最後,討論了基於AI的安全監控方法在醫療領域的應用。

本書採用了理論與實踐相結合的方法,使讀者能夠輕鬆理解複雜的主題和概念,並透過真實情境進行學習。

作者簡介

Massimo Ficco is Full Professor at the Computer Science Department of the University of Salerno, Italy. His major research interests include security and reliability aspects of critical infrastructures. Currently, his scientific research and dissemination activities concern the use of machine learning and artificial intelligence in the context of malware analysis and IoT systems. He has published more than 150 papers.

作者簡介(中文翻譯)

Massimo Ficco 是義大利薩萊諾大學計算機科學系的全職教授。他的主要研究興趣包括關鍵基礎設施的安全性和可靠性方面。目前,他的科學研究和推廣活動涉及在惡意軟體分析和物聯網系統中使用機器學習和人工智慧。他已發表超過 150 篇論文。