Call for Papers

Scope

Modern ICT systems are recognised as cost-effective environments for outsourcing infrastructure, platforms and software. The problems related to privacy and security are still challenging. ICT systems end-users are now using applications that fall under the data-intensive paradigm, such as Skyline queries, streaming information relays, and crowd-sourced disaster management. Cyber Modelling and Simulation (M&S) is a collection of models, frameworks, and other tools through which researchers, engineers, and technologists can practice the science of cybersecurity. However, the above paradigm shift has opened newer research directions in security, data interoperability, sustainable software development and many other areas.

 This track primarily encompasses practical approaches that advance research in securely handling large amounts of data in the cloud, mobile nodes, and cloud-connected edge clusters such as MANETs, wireless sensor networks, AI systems, and other ITC systems. Successful contributions may range from advanced technologies, applications and innovative solutions for secure ITC to developing methods and conceptual and theoretical models related to secure management, monitoring, scheduling and resource allocation.

Recommended topic areas include, but are not limited to:

• M&S of security-aware data gathering and assimilation in ICT systems

• Cloud, edge and fog-secure models and infrastructures

• M&S of secure multi-agent systems

• Machine learning-based models and simulators of secure ICT systems

• Advanced security and privacy mechanisms in mobile and distributed infrastructures

• Scalable identity and authentication protocols in ICT systems

• Secure resource allocation and scheduling in computing networks

• Secure communication in Smart Grid installations using Ad Hoc Network Protocols

• Wireless Sensor Node applications for Smart Grid

• Secure 5G applications for Smart Grid

• Economic models in secure ICT environments

• Secure mobile network applications

• Trust and Reputation Management in ICT Systems

•  M&S of attacks on machine learning models