Cryptography: Boolean functions and related problems
Offered By: Novosibirsk State University via Coursera
Course Description
Overview
The course invites you to learn more about cryptography; you'll learn some important math which stands behind the ciphers, and defines how resistant the particular cipher will be to different types of attacks.
The key topics covered in the course:
* how cryptography developed in Russia and in the Soviet Union, including the facts which used to be top secret until very recent times;
* Boolean functions and S-boxes, and how the resistance of a cipher depends on a cryptographic properties of a Boolean function;
* methods of cryptanalysis
* some special and most intriguing types of cryptographic Boolean functions: bent functions and APN-functions (Almost Perfect Nonlinear Functions)
* AI and ML for cryptography.
Welcome to the course, and enjoy your learning!
Learn more about NSU programs: https://english.nsu.ru/admission/programs/master-s-degree-programs-english/quantum-technologies-and-cryptography-en/
The key topics covered in the course:
* how cryptography developed in Russia and in the Soviet Union, including the facts which used to be top secret until very recent times;
* Boolean functions and S-boxes, and how the resistance of a cipher depends on a cryptographic properties of a Boolean function;
* methods of cryptanalysis
* some special and most intriguing types of cryptographic Boolean functions: bent functions and APN-functions (Almost Perfect Nonlinear Functions)
* AI and ML for cryptography.
Welcome to the course, and enjoy your learning!
Learn more about NSU programs: https://english.nsu.ru/admission/programs/master-s-degree-programs-english/quantum-technologies-and-cryptography-en/
Syllabus
- Introduction
- S-Boxes and artificial intelligence
- Bent functions: results and applications
- Almost Perfect Nonlinear functions
- Foundations of quantum key distribution
Taught by
Natalia Tokareva, Anastasiya Gorodilova, George Pintus, Stjepan Picek and Kutsenko Aleksandr
Tags
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent