Ernesto Damiani
Securing Data Pipelines along the Cloud Continuum: The MUSA approach
Brief:
In the past decade, many organizations have re-designed their operation by migrating their key business processes (to name but a few, procurement, supply chains, Human Resources management) to global public clouds, where scalability and cost flexibility could be achieved. Today, a new wave of Digital Transformation is changing again how people live, consume and work. Processes in key domains like transportation, supply chain management and healthcare need to provide low latency, high throughput and distributed access. Furthermore, their execution needs to take place within well-specified perimeters supporting traffic segregation, in order to guarantee data protection. security and resilience. The 5G architecture promises to fulfill these new requirements, supporting a “Cloud Continuum” that allows for the deployment of micro-services on the 5G operators core networks (edge-on-network) as a complement to classic edge-on-premises and cloud options. Based on the approach of the MUSA project to delivering open science research pipelines over 5G, the talk discusses the open challenges that need to be tackled to keep this promise, from the instrumentation of the 5G infrastructure to support for securing services and process orchestrations along the continuum.
Short Bio:
Ernesto Damiani is a Full Professor at Università degli Studi di Milano (Italy), Senior Director of the Robotics and Intelligent Systems Institute, and Director of Center for Cyber Physical Systems (C2PS) within Khalifa University (UAE). He is the leader of the Big Data area at Etisalat British Telecom Innovation Center (EBTIC), and President of the Consortium of Italian Computer Science Universities (CINI). He is also part of the ENISA Ad-Hoc Working Group on Artificial Intelligence Cybersecurity. Ernesto’s areas of interest include cyber-physical systems, Big Data Analytics, Edge/Cloud security and performance, Artificial Intelligence, and Machine Learning. Ernesto Damiani has pioneered model-driven data analytics. He has authored more than 670 Scopus-indexed publications and several patents. Ernesto has been a recipient of the Research and Innovation Award from the IEEE Technical Committee on Homeland Security , of the Stephen Yau Award from the Service Society, of the Outstanding contributions Award from IFIP TC2, of the Chester-Sall Award from IEEE IES, of the IEEE TCHS Research and Innovation Award, and of a doctorate honoris causa from INSA – Lyon (France) for his contribution to Big Data teaching and research.