14035 - Application of Side-Channel Analysis Methods in the Earlier Design Phase of Cryptographic Implementations Modulübersicht
Module Number: | 14035 |
Module Title: | Application of Side-Channel Analysis Methods in the Earlier Design Phase of Cryptographic Implementations |
Anwendung von Seitenkanalanalyse-Methoden in der frühen Entwurfsphase kryptographischer Designs | |
Department: | Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology |
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Language of Teaching / Examination: | English |
Duration: | 1 semester |
Frequency of Offer: | Every winter semester |
Credits: | 6 |
Learning Outcome: | Upon completion of the module, students will be familiar with various statistical, machine learning, and clustering methods for analyzing side-channel leakage sources. They are able to apply these methods and evaluate and comparatively discuss their effectiveness in extracting secret data.They will be able to use, understand, and describe selected methods for analyzing a given set of traces. They understand the applicability of the analysis methods as a means to determine the vulnerability of cryptographic designs in their early design phase, using the example of a hardware accelerator of elliptic curve point multiplication for an elliptic curve cryptosystem. |
Contents: | This course covers both theoretical and practical aspects of applying statistical and machine learning methods as a means of extracting secret data for side-channel attacks. Selected statistical as well as clustering methods will be presented and described. The suitability of the methods for determining side-channel leakage sources in attacked designs is discussed. Furthermore, selected countermeasures against physical attacks are presented and their effectiveness is discussed. Main topics covered are:
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Recommended Prerequisites: | None |
Mandatory Prerequisites: | Passed exam of module:
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Module Examination: | Continuous Assessment (MCA) |
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Evaluation of Module Examination: | Performance Verification – graded |
Limited Number of Participants: | 10 |
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