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      Side-Channel Analysis of Embedded Systems: An Efficient Algorithmic Approach

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      SKU 9783030772215 Categories ,
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      They aim at extracting secrets from embedded systems while they execute cryptographic algorithms, and they consist of two steps, measurement and analysis. They present all known analyses within the same notation framework, which allows the reader to rapidly understand and lear...

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      Description

      Product ID:9783030772215
      Product Form:Hardback
      Country of Manufacture:GB
      Title:Side-Channel Analysis of Embedded Systems
      Subtitle:An Efficient Algorithmic Approach
      Authors:Author: Maamar Ouladj, Sylvain Guilley
      Page Count:153
      Subjects:Coding theory and cryptology, Coding theory & cryptology, Electronics: circuits and components, Communications engineering / telecommunications, Databases, Computer security, Circuits & components, Communications engineering / telecommunications, Databases, Computer security
      Description:Select Guide Rating
      They aim at extracting secrets from embedded systems while they execute cryptographic algorithms, and they consist of two steps, measurement and analysis. They present all known analyses within the same notation framework, which allows the reader to rapidly understand and learn contrasting approaches.
      It has been more than 20 years since the seminal publications on side-channel attacks. They aim at extracting secrets from embedded systems while they execute cryptographic algorithms, and they consist of two steps, measurement and analysis. This book tackles the analysis part, especially under situations where the targeted device is protected by random masking. The authors explain advances in the field and provide the reader with mathematical formalizations. They present all known analyses within the same notation framework, which allows the reader to rapidly understand and learn contrasting approaches. It will be useful as a graduate level introduction, also for self-study by researchers and professionals, and the examples are taken from real-world datasets.
      Imprint Name:Springer Nature Switzerland AG
      Publisher Name:Springer Nature Switzerland AG
      Country of Publication:GB
      Publishing Date:2021-07-29

      Additional information

      Weight426 g
      Dimensions164 × 242 × 19 mm