Cryptology For Engineers: An Application-oriented Mathematical Introduction
Language: English
Published by WSPC, 2020
- Softcover
- New

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- Title
- Cryptology For Engineers: An Application-oriented Mathematical Introduction
- Author
- Schmied, Robert
- Publisher
- WSPC
- Publication year
- 2020
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 9819832756
- ISBN 13
- 9789819832750
Cryptology is increasingly becoming one of the most essential topics of interest in everyday life. Digital communication happens by transferring data between at least two participants — But do we want to disclose private information while executing a sensitive bank transfer? How about allowing third-party entities to eavesdrop on private calls while performing an important secret business discussion? Do we want to allow ambient communication concerning us to be manipulated while control software is driving our autonomous car along a steep slope? Questions like these make it clear why issues of security are a great concern in our increasingly augmented world. Cryptology for Engineers is a study of digital security in communications systems. The book covers the cryptographical functionalities of ciphering, hash generation, digital signature generation, key management and random number generation, with a clear sense of the mathematical background on the one hand and engineers' requirements on the other. Numerous examples computable by hand or with a small additional cost in most cases are provided inside.
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About the Author
Robert Schmied is a scientist at Bundeswehr University Munich, Department of Electrical Engineering and Information Technology. Since his doctoral graduation he has been gaining experience in teaching cryptology and data science for many years which are both his work priorities and main fields of research at the chair of mathematics. In data science he is influenced by the ideas of exploratory data analysis which is more relevant than ever in a new guise. In cryptology, he deals with Shannon entropy-based, statistical text analysis.
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