Keynote Speaker: GIUSEPPE BIANCHI,  University of Roma - Tor Vergata, Italy

Keynote Title: Sketch-based measurements: from discrete-time batching to continuous-time operation 

Biography: Giuseppe Bianchi is Full Professor of Networking at the University of Roma Tor Vergata since 2007. His research activity includes wireless networks (his pioneering research work on WLAN modelling and assessment has received the ACM SigMobile 2017 Test-Of-Time award), programmable network systems, privacy and security, traffic modelling and control, and is documented in about 300 peer-reviewed international journal and conference papers, accounting for more than 20.000 citations (source: Google Scholar). He has coordinated six large scale EU projects, and has been  editor for several journals in his field, including IEEE/ACM Trans. on Networking, IEEE Trans. on Wireless Communications, IEEE Trans. on Network and Service Management, and Elsevier Computer Communications. 

Abstract: many network-related measurement activities do exploit highly optimized ultra-compact data structures, often referred to as "sketches". While a huge amount of work has so far focused on their investigation from the classical perspective of performance/memory-footprint trade-offs, a somewhat more limited attention has been spent on how sketches should be integrated in continuous-time monitoring tasks, especially when the classical approach of batching measurements into fixed-size windows may not perfectly fit with the requirements of the monitoring task at hands. In the talk we will discuss this issue, and we will present a few continuous-time/near-continuous-time constructions, tackling either count-min sketch extensions as well as loglog counters. 

Keynote Speaker: FALKO DRESSLER,  Technische Universität,  Berlin , Germany

Keynote Title: Reinforcement Learning Approaches in Virtalized Edge Computing  

Biography: Falko Dressler is full professor and Chair for Telecommunication Networks at the School of Electrical Engineering and Computer Science, TU Berlin. He received his M.Sc. and Ph.D. degrees from the Dept. of Computer Science, University of Erlangen in 1998 and 2003, respectively. Dr. Dressler has been associate editor-in-chief for IEEE Trans. on Mobile Computing and Elsevier Computer Communications as well as an editor for journals such as IEEE/ACM Trans. on Networking, IEEE Trans. on Network Science and Engineering, Elsevier Ad Hoc Networks, and Elsevier Nano Communication Networks. He has been chairing conferences such as IEEE INFOCOM, ACM MobiSys, ACM MobiHoc, IEEE VNC, IEEE GLOBECOM. He authored the textbooks Self-Organization in Sensor and Actor Networks published by Wiley & Sons and Vehicular Networking published by Cambridge University Press. He has been an IEEE Distinguished Lecturer as well as an ACM Distinguished Speaker. Dr. Dressler is an IEEE Fellow as well as an ACM Distinguished Member. He is a member of the German National Academy of Science and Engineering (acatech). He has been serving on the IEEE COMSOC Conference Council and the ACM SIGMOBILE Executive Committee. His research objectives include adaptive wireless networking (sub-6GHz, mmWave, visible light, molecular communication) and wireless-based sensing with applications in ad hoc and sensor networks, the Internet of Things, and Cyber-Physical Systems. 

Abstract: We will discuss the challenges and opportunities of distributed data management solutions ranging from the mobile edge to the data centers. Modern 5G networks promise to provide all means for communication in this domain, particularly when integrating Mobile Edge Computing (MEC). However, it turns out that despite the many advantages, it is unlikely that such services will be provided with sufficient coverage. As a novel concept, virtualized edge computing (V-Edge) have been proposed that bridges this gap. We present a learning based approach to make such an V-Edge resilient to dynamics, failures, and even malicious attacks. In particular, we contrast centralized and federated learning approaches and reinforcement based approaches. 

Keynote Speaker: JOCHEN SCHILLER,  Freie Universität,  Berlin , Germany

Keynote Title: AI, IoT, Networks, Security, Cyberwar – is history repeating or do we get it right this time?  

Biography: Prof. Dr.-Ing. Jochen H. Schiller (jochen.schiller@fu-berlin.de) is full professor responsible for Computer Systems & Telematics at the Institute of Computer Science, Freie Universitaet Berlin, Germany. From 2003 to 2007 and 2015 to 2019 Dr. Schiller was Dean of the Department for Mathematics and Computer Science. From 2007 until 2010 he was Vice President of the Freie Universitaet Berlin. From 2009 until 2015 Dr. Schiller was head of the Research Center for Public Safety and Security at the Freie Universitaet. In April 2012 he founded the Innovation Center Public Safety and Security at Fraunhofer FOKUS. From April 2017 until March 2023 Dr. Schiller was board member of the Einstein Center Digital Future in Berlin responsible for digital industries and services. Since 2023 he is CIO of Freie Universitaet Berlin. His research focus is on wireless, mobile, and embedded devices, communication protocols, operating systems for devices with small footprint, and security aspects of mobile communication systems. Up to now, Dr. Schiller published 5 books and more than 200 international peer-reviewed papers.  

Abstract: "We've been at war for a long time!" - This phrase is heard again and again in connection with cyberspace, i.e. the virtual space that is spanned by global communication networks and to which we are all connected via the most diverse systems - from energy supply to banks to our smartphones. Attacks on our (critical) infrastructure are commonplace and affect a wide variety of systems from manufacturing industries to hospitals to educational institutions. The talk will primarily present from a technical perspective where and why we are vulnerable and what countermeasures are needed from both a technical and a legislative perspective – and why this all matters for us developing cool and fancy new systems. 

Keynote Speaker: Gerhard Wunder,  Freie Universität,  Berlin , Germany

Keynote Title: How to Provably Generate Privacy-Preserving Synthetic Data for the Data Economy

Biography: Gerhard Wunder is Cybersecurity & AI Professor at Freie Universität Berlin since 2021, Heisenberg Fellow of the 'Deutsche Forschungsgemeinschaft' (DFG), co-initiator of the Center of Trustworthy AI (www.zvki.de) and advising German ministries on AI & Cybersecurity policies. Before that, Gerhard Wunder led a research group at Fraunhofer Heinrich-Hertz-Institut in Berlin, and held visiting professor positions at the Georgia Institute of Technology in Atlanta (USA, GA), and Stanford University in Palo Alto (USA CA). 

Abstract: Synthetic data has been hailed as the silver bullet for privacy preserving data analysis. If a record is not real, then how could it violate a person's privacy? In addition, deep-learning based generative models are employed successfully to approximate complex high-dimensional distributions from data and draw realistic samples from this learned distribution. It is often overlooked though that generative models are prone to memorizing many details of individual training records and often generate synthetic data that too closely resembles the underlying sensitive training data, hence violating strong privacy regulations as, e.g., encountered in health care. In this talk we explore alternative approaches for privately generating data that makes direct use of the inherent stochasticity in generative models. The main idea is to appropriately constrain the continuity modulus of the deep models instead of adding another noise mechanism on top. For this approach, we derive mathematically rigorous privacy guarantees and illustrate its effectiveness with practical experiments.