相關主題
商品描述
Noisy data appears very naturally in applications where the authentication is based on physical identifiers, such as human beings, or physical structures, such as physical unclonable functions. This book examines how the presence of noise has an impact on information security, describes how it can be dealt with and possibly used to generate an advantage over traditional approaches, and provides a self-contained overview of the techniques and applications of security based on noisy data.
Security with Noisy Data thoroughly covers the theory of authentication based on noisy data and shows it in practice as a key tool for preventing counterfeiting. Part I discusses security primitives that allow noisy inputs, and Part II focuses on the practical applications of the methods discussed in the first part.
Key features:
• Contains algorithms to derive secure keys from noisy data, in particular from physical unclonable functions and biometrics - as well as the theory proving that those algorithms are secure
• Offers practical implementations of algorithms, including techniques that give insight into system security
• Includes an overview and detailed description of new applications made possible by using these new algorithms
• Discusses recent theoretical as well as application-oriented developments in the field, combining noisy data with cryptography
• Describes the foundations of the subject in a clear, accessible and reader-friendly style
• Presents the principles of key establishment and multiparty computation over noisy channels
• Provides a detailed overview of the building blocks of cryptography for noisy data and explains how these techniques can be applied, (for example as anti-counterfeiting and key storage)
• Introduces privacy protected biometric systems, analyzes the theoretical and practical properties of PUFs and discusses PUF based systems
• Addresses biometrics and physical unclonable functions extensively
This comprehensive introduction offers an excellent foundation to graduate students and researchers entering the field, and will also benefit professionals needing to expand their knowledge. Readers will gain a well-rounded and broad understanding of the topic through the insight it provides into both theory and practice.
Pim Tuyls is a Principal Scientist at Philips Research and a Visiting Professor at the COSIC Department of the Katholieke Universiteit of Leuven, Dr Boris Skoric and Dr Tom Kevenaar are research scientists at Philips Research Laboratories, Eindhoven.
商品描述(中文翻譯)
雜訊數據在基於物理識別符的應用中非常自然地出現，例如人類或物理結構，如物理不可複製功能（PUF）。本書探討雜訊的存在如何影響資訊安全，描述如何處理這些雜訊並可能利用其相對於傳統方法的優勢，並提供一個獨立的概述，介紹基於雜訊數據的安全技術和應用。
《雜訊數據的安全性》徹底涵蓋了基於雜訊數據的身份驗證理論，並展示其作為防止偽造的關鍵工具的實際應用。第一部分討論允許雜訊輸入的安全原語，第二部分則專注於第一部分中討論的方法的實際應用。
主要特點：
• 包含從雜訊數據中推導安全密鑰的算法，特別是來自物理不可複製功能和生物識別技術的算法，以及證明這些算法安全性的理論
• 提供算法的實際實現，包括提供系統安全性見解的技術
• 包括使用這些新算法所實現的新應用的概述和詳細描述
• 討論該領域最近的理論和應用導向的發展，將雜訊數據與密碼學結合
• 以清晰、易於理解和讀者友好的風格描述該主題的基礎
• 提出在雜訊通道上建立密鑰和多方計算的原則
• 提供雜訊數據密碼學的基本組件的詳細概述，並解釋這些技術如何應用（例如作為防偽和密鑰存儲）
• 介紹隱私保護的生物識別系統，分析PUF的理論和實際特性，並討論基於PUF的系統
• 廣泛探討生物識別技術和物理不可複製功能
這本全面的介紹為進入該領域的研究生和研究人員提供了優秀的基礎，並將使需要擴展知識的專業人士受益。讀者將通過本書提供的理論和實踐見解，獲得對該主題的全面和廣泛的理解。
Pim Tuyls是飛利浦研究的首席科學家，也是魯汀大學COSIC系的客座教授，Boris Skoric博士和Tom Kevenaar博士是飛利浦研究實驗室的研究科學家，位於埃因霍溫。
