ARTISAN PHD SUMMER SCHOOL - ARTificial Intelligence in Secure ApplicatioNs

WEB SITE: https://artisan2023.sciencesconf.org/

DATES: 17-20 July 2023

VENUE: Wien, Austria

REGISTRATION FEE: 420 Euros incl. VAT (covers lunches, coffee breaks, social dinner)

CONTACTS: artisan2023@scienceconf.org

The ARTISAN PhD Summer School (Role and effects of ARTificial Intelligence in Secure ApplicatioNs) tackles the issues related to Artificial Intelligence (AI) and Machine Learning (ML) with regards to security and safety applications.

The last years have witnessed an increasing adoption of AI and especially ML techniques in many automated systems covering almost all the main domains of our lives. AI-based components are performing complex tasks such as pattern recognition, image recognition, and even control, and are more and more being used in security-critical and safety-critical systems, with evident examples in domains like automotive, industrial automation, and energy systems, among others. The objective of ARTISAN is to illustrate what are the foundations, applications, benefits, misuse, and related effects of the application of AI and ML in security-critical systems and infrastructures. ARTISAN aims to explain how AI/ML is a double-edged sword that can either enhance security or expose novel security threats.

In ARTISAN, AI and ML are addressed as i) means to improve the security of target systems and applications; ii) means to attack applications; iii) an enabling technology that is beneficial to build innovative systems and applications, but that can expose itself to novel vulnerabilities.

The school is mostly intended for Ph.D. Students in Computer Science and Engineering, and it includes foundations, techniques, industrial applications, and ethical and legal considerations.


LIST OF SPEAKERS AND TOPICS
- Foundations of AI - Danilo Giordano (Politecnico di Torino, Italy)

- Domain generation algorithms (DGA) detection using ML - Francesca Soro (Austrian Institue of Technology, Austria)

- Towards Machine Learning Models that We Can Trust: Hacking and (properly) Testing AI - Maura Pintor (University of Cagliari, Italy)

- Meta-Learning for Intrusion Detection: Teamwork or Fight against each other? - Tommaso Zoppi (University of Florence, Italy)

- Dependability Challenges in Safety-Critical Systems: the adoption of Machine learning - Andrea Bondavalli (University of Florence, Italy)

- Fake News Detection - Alexander Schindler (Austrian Institue of Technology, Austria)

- AI recursiveness and virtue - Wessel Reijers (University of Wien, Austria)

- Applications: Safety architectures for self-driving cars - Wilfried Steiner (TTTech, Austria)

- Applications: ML for Cybersecurity in converged energy systems: a saviour or a villain? - Angelos Marnerides (Glasgow University, UK)

- Applications: Security & Safety Issues in the Operation of autonomous passenger vehicles in public roads - Javier Ibanez-Guzman (Renault S.A. Research Division, France)

- Data security and privacy – Speaker To Be Announced


ORGANIZING COMMITTEE
- Oliver Jung, Austrian Institute of Technology, Austria
- Oum-El-Kheir Aktouf, Grenoble INP - UGA, France
- Andrea Ceccarelli, University of Florence, Italy


COMMUNICATION AND PUBLICITY
- Oum-El-Kheir Aktouf, Grenoble INP - UGA, France
- Annabelle Mercier, Université Grenoble Alpes, France