YoVDO

New Slide Attacks on Almost Self-Similar Ciphers

Offered By: TheIACR via YouTube

Tags

Cryptanalysis Courses Cryptography Courses

Course Description

Overview

Explore new slide attacks on almost self-similar ciphers in this 38-minute conference talk presented at Eurocrypt 2020. Delve into the paper by Orr Dunkelman, Nathan Keller, Noam Lasry, and Adi Shamir, which introduces novel techniques for cryptanalysis. Learn about the basics of slide attacks, their extensions, and generalizations. Examine applications of slide attacks on various ciphers, including a generic SPN (1K-AES). Understand the basic assumptions of slide attacks and how they can be circumvented. Investigate the concept of slid sets for attacking 2K-AES and techniques for matching these sets. Discover methods for attacking 1K-AES with secret S-boxes and incomplete diffusion in the last round. Gain insights into suggestive plaintext structures and substitution slide attacks. Enhance your knowledge of cryptographic vulnerabilities and advanced attack strategies in this comprehensive presentation.

Syllabus

Intro
Outline 1 Introduction Slide Attacks
Slide Attacks (BW99) (cont.)
Other Extensions and Generalizations
Several Applications of Slide Attacks
A Generic SPN (1K-AES)
A Slide Attack on 1K-AES B+18
The Basic Assumption of Slide Attacks
Last Round Function → No Slid Chains
Not All SPNs are the Same
Slid Sets for Attacking 2K-AES
Matching the Slid Sets
Attacking 1K-AES with Secret S-boxes
Suggestive Plaintext Structures (cont.)
Attacking 1K-AES with Incomplete Diffusion in the Last Round
Substitution Slide Attack (Cont.)
Summary


Taught by

TheIACR

Related Courses

Internetwork Security
Indian Institute of Technology, Kharagpur via Swayam
Classical Cryptosystems and Core Concepts
University of Colorado System via Coursera
Cryptography and Information Theory
University of Colorado System via Coursera
Cryptography And Network Security
Indian Institute of Technology, Kharagpur via Swayam
An Introduction to Cryptography
Coventry University via FutureLearn