STAM

Distributed computer networked systems and services have become a crucial infrastructure element for the organization of modern society. These networks and services are required to be more and more open and new technology is designed to facilitate the interoperation between these networks composed of heterogeneous, communicating devices. Guaranteeing that they interoperate in a secure way has become a major concern for individuals, enterprises and governments.

Since the environment may be potentially hostile and contain malicious components, it is crucial to define frameworks adapted to distributed systems to enforce security and privacy. By distributed systems, we mean all systems that are composed of more than one communicating device such as telecommunication networks, cloud/Edge computer environment, industrial systems, smart communities, internet of things, distributed operating systems and middleware etc.

The STAM workshop tries to answer how miss-behaviours and attacks modeling can help users understand the occurrence of malicious behaviors in order to avoid them, and what are the advantages and drawbacks of the existing models. At the same time, the workshop tries to understand how to solve the challenging security testing and monitoring problem given that testing distributed systems is a complex task and security and artificial intelligence will add new challenges and difficulties to be solved.

The objective of this workshop is to share ideas, methods, techniques, and tools about security testing and monitoring in distributed systems to improve the state of the art. In addition to scientific paper presentations, we intend to have one or two keynotes describing ongoing activities in the related areas and demonstrations of some innovative security tools.

STAM workshop is supported by projects:
HE-AI4Cyber
HE-DETERMINISTIC6G
HE-DYNABIC
HE-NERO
HE-RESILMESH
HE-NATWORK
H2020-ECSEL AIDOART

The goal of STAM workshop is to bring together safety & security practitioners and researchers to exchange ideas, perspectives on problems, and solutions. Papers proposing novel models, methods, and algorithms are welcomed as well as papers reporting experiences on the application of existing methods on case studies and industrial examples.