International Summer School in Cryptology and Cyber-Resilience
8 – 15 July 2018 (Sunday-Sunday), “National Institute of Education”, Oriahovitza, Bulgaria
(view more about the location)
Registration is open until June 20th! >>> to download the registration form, click here.
CryptoBG*2018 First announcement >>> download from here
CryptoBG*2018 Sponsorship package >>> download from here
Queries and interest >>> info (at) cryptoBG (dot) org
One intensive week of theory, practice and discussions: 4-hour lectures and tutorials by international experts extended with practical workshops, labs and seminars, simulations, round-table discussions and working groups on hot topics
Topics of the year:
- Symmetric Encryption
- White-Box Cryptogaphy
- Secure Multi-Party Computation
- Deep Learning
And a round of CTF*BG (Capture The Flag) by the CyResLab of ESI CEE – RED <>BLUE teams in 3 sessions:
- CTF “warm up” & challenges explained
- Active security
- CTF*BG Ultimate
Especially for the Industry and Sponsors: Challenge the CryptoBG*2018 team – define a problem/challenge, bring it on day 1 and get a solution in a week
Lectures and Tutorials
Dr. Claude Barral (Bactech, France) – Evaluation of biometric systems: who said straightforward?
We will discuss all the issues one may face while setting up an evaluation environment for any biometric systems: which biometric data is targeted? How many different security settings? What is a representative database? Public vs Private databases? Target database size and architecture? How many authentication tests needed to claim a 0,001% false acceptance rate?
Which evaluation target: Compliance? Interoperability? Security? Performances? Well, definitely not straightforward indeed! You will see…
Dr. Julien Bringer (Smart Valor, Switzerland) – Blockchain
Dr. Nadia El Mrabet (ENSMSE, France) – Introduction to Cryptography
Dr. Nicolas Gama (Inpher, Switzerland) – Privacy Preserving Computation
Dr. Pascal Paillier (CryptoExperts, France) – White-Box Cryptography
Dr. Adrian Thillard (ANSSI, France) –Deep Learning Techniques for Side-Channel Analysis
Deep learning methods are a subclass of machine learning algorithms based on multiple layers of nonlinear processing units for feature extraction and transformation. These methods have been successfully used in the recent years in many fields, such as image recognition, speech recognition, bioinformatics, or even chess and go.
During this tutorial, we will start with a description of the main steps of side-channel attacks, and highlight the distinction between profiled and non-profiled side-channel attacks.
We will then introduce the basics of Multi-Layer Perceptrons and Convolutional Neural Networks, and illustrate how these algorithms can be used to automatically solve some problems encountered by a side-channel evaluator.
Working on a public database of real side-channel acquisitions, we will apply those methods to retrieve the secret key. To do so, we will be using the Keras library on top of Google’s Tensorflow, allowing us to build layer by layer a neural network. We will then train our network and use it to predict the correct manipulated values. We will then study the relevance and impact of hyperparameters on our results, and compare its performance against classical side-channel approaches.
Adrián Ranea (KU Leuven, Belgium) – Affine Encodings for White-Box Cryptography
Ilia Dafchev (Telelink, Bulgaria) – Practical Malware Analysis of the Crysis/Dharma Ransomware