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出版商:
Springer
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出版日期:
2026-04-11
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售價:
$7,030
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貴賓價:
9.5 折
$6,678
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語言:
英文
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頁數:
453
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裝訂:
Hardcover - also called cloth, retail trade, or trade
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ISBN:
3032111528
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ISBN-13:
9783032111524
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相關分類:
量子計算
商品描述
This book surveys state-of-the-art research on adversarial robustness of quantum machine learning algorithms. Despite their high efficiency and accuracy, classical ML and AI algorithms can be easily fooled by an adversary through manipulation or spoofing of data (also known as adversarial attacks), which poses serious security ramifications. On the other hand, the integration of quantum computing in ML and AI is progressing rapidly to create new quantum ML/AI models which are designed to fundamentally exploit quantum mechanical properties to gain advantages in aspects such as training speed or feature extraction accuracy. This raises the important question of whether quantum AI algorithms are as vulnerable as classical AI models. Recent work has shown that quantum AI algorithms are remarkably robust against adversarial attacks. This offers a unique opportunity to leverage quantum computing, specifically its unique properties like superposition and entanglement, to develop highly resistant quantum AI systems. This shift is crucial for enhancing the safety and reliability of AI in security-sensitive applications. This book provides a comprehensive overview of the research in the emerging field of quantum adversarial AI, presenting seminal work from world-leading quantum AI experts on quantum AI and its benchmarking against adversarial attacks. It provides an essential reference for graduate students and industry experts who are interested in quantum AI for security-sensitive autonomous systems.
商品描述(中文翻譯)
本書調查了量子機器學習算法在對抗性穩健性方面的最先進研究。儘管傳統的機器學習（ML）和人工智慧（AI）算法具有高效率和高準確性，但它們很容易受到對手的數據操控或欺騙（也稱為對抗性攻擊），這對安全性造成了嚴重的影響。另一方面，量子計算在機器學習和人工智慧中的整合正在迅速發展，旨在創建新的量子機器學習/人工智慧模型，這些模型設計上根本上利用量子力學特性，以在訓練速度或特徵提取準確性等方面獲得優勢。這引發了一個重要問題：量子人工智慧算法是否和傳統人工智慧模型一樣脆弱。最近的研究顯示，量子人工智慧算法對對抗性攻擊具有顯著的穩健性。這提供了一個獨特的機會，可以利用量子計算，特別是其獨特的特性，如疊加和糾纏，來開發高度抗干擾的量子人工智慧系統。這一轉變對於增強在安全敏感應用中人工智慧的安全性和可靠性至關重要。本書提供了量子對抗性人工智慧新興領域的綜合概述，展示了來自世界領先的量子人工智慧專家的開創性研究，並對量子人工智慧及其在對抗性攻擊中的基準進行了介紹。這是對於有興趣於安全敏感自主系統的研究生和行業專家的重要參考資料。
作者簡介
Professor Muhammad Usman is Head of Quantum Systems and Principal Staff Member at CSIRO's Data61 which is Australia National Research Organisation. He has over 15 years of research and teaching experience in the field of quantum computing with a track-record of over 120 research papers in high-impact international journals. At CSIRO, Professor Usman is leading a team of over 20 researchers working at the forefront of quantum algorithms, quantum software engineering, and quantum security. He is a fellow of the Australian Institute of Physics and serves on the executive editorial boards of two international journals (Nature Scientific Reports and IOP Nano Futures), a committee member of Standards Australia to help in standardisation of quantum technologies and have academic affiliations at the University of Melbourne and RMIT University. Professor Usman is the chair of organising committee of international conference on Quantum Techniques in Machine Learning 2024 (now serves on the Steering Committee), has delivered numerous invited talks in international conferences and has been invited on several panel discussions at national and international meetings. He was received the State of Victoria iAward 2024, Innovative of the Year 2023 Award by Defence Industry, Winner of the Australian Army Quantum Technology Challenge in three years in a row (2021, 2022 and 2023), Rising Stars in Computational Materials Science by Elsevier in 2020, and Dean's Award for Excellence in Research (Early Career) at the University of Melbourne in 2019. Professor Usman is a recipient of prestigious international research fellowships from Fulbright USA (20005-2010) and DAAD Germany in 2010. Professor Usman is a passionate quantum educator and has been promoting quantum education among school children as part of the CSIRO's STEM Scientists in Schools program.
作者簡介(中文翻譯)
穆罕默德·烏斯曼教授是澳洲國家研究機構CSIRO的Data61部門的量子系統負責人及主要成員。他在量子計算領域擁有超過15年的研究和教學經驗，並在高影響力的國際期刊上發表了超過120篇研究論文。在CSIRO，烏斯曼教授領導著一支由20多位研究人員組成的團隊，專注於量子演算法、量子軟體工程和量子安全的前沿研究。他是澳洲物理學會的會員，並擔任兩本國際期刊（《Nature Scientific Reports》和《IOP Nano Futures》）的執行編輯委員會成員，還是澳洲標準協會的委員，協助量子技術的標準化，並在墨爾本大學和RMIT大學擁有學術聯繫。烏斯曼教授是2024年國際會議「量子技術在機器學習中的應用」的組織委員會主席（目前擔任指導委員會成員），並在多個國際會議上發表了多場受邀演講，還受邀參加多個國內外會議的專題討論。他於2024年獲得維多利亞州iAward，2023年獲得國防工業年度創新獎，連續三年（2021、2022和2023年）贏得澳洲陸軍量子技術挑戰賽，2020年被Elsevier評選為計算材料科學的明日之星，並於2019年在墨爾本大學獲得研究卓越獎（早期職業）。烏斯曼教授是美國富布賴特（Fulbright USA，2005-2010）和德國DAAD於2010年頒發的國際研究獎學金的獲得者。他是一位熱情的量子教育者，並作為CSIRO的STEM科學家進入學校計畫的一部分，推廣量子教育給學童。
