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Keynote Lectures

Leveraging Blockchain Technology to Enhance Security and Privacy in the Internet of Things
Sokratis K. Katsikas, Norwegian University of Science and Technology, Norway

Jump, Crawl, Attract, Propagate: Security Challenges in Emerging Communication Networks
Stefan Schmid, University of Vienna, Austria

Backdooring Deep Learning Architectures: Threats and (some) Opportunities
Mauro Barni, Università di Siena, Italy


Leveraging Blockchain Technology to Enhance Security and Privacy in the Internet of Things

Sokratis Katsikas
Norwegian University of Science and Technology

Brief Bio
Sokratis K. Katsikas was born in Athens, Greece, in 1960. He received the Diploma in Electrical Engineering from the University of Patras, Patras, Greece in 1982, the Master of Science in Electrical & Computer Engineering degree from the University of Massachusetts at Amherst, Amherst, USA, in 1984 and the Ph.D. in Computer Engineering & Informatics from the University of Patras, Patras, Greece in 1987. In 2019 he has awarded a Doctorate Honoris Causa by the Dept. of Production and Management Engineering of the Democritus University of Thrace, Greece. He is the Rector of the Open University of Cyprus, Nicosia, Cyprus, and Professor with the Center for Cyber and Information Security, Department of Information Security and Communications, Norwegian University of Science and Technology, Norway. His research interests lie in the areas of information and communication systems security and of estimation theory and its applications. His research activity over the past 30 years has resulted in the publication of 39 books; 35 book chapters; 86 journal publications (of which 9 invited); and 130 publications in conference proceedings (of which 30 invited). According to Googlescholar, his research work has been cited 3.085 times and his h-index is 27. He has participated in more than 60 funded national and international R&D projects in his areas of research interest. He is serving on the editorial board of several scientific journals, and has served on/chaired the technical programme committee of more than 600 international scientific conferences. He chairs the Steering Committee of the ESORICS Conferences.

The Internet of Things (IoT) and Blockchain are two technologies that have dramatically changed the traditional computing models. While the IoT has enabled multiple new computing applications, it has also raised significant issues regarding security and privacy, as lightweight devices with limited resources, scattered in terms of network topology and too diverse in terms of hardware and software are nowadays used for processing huge amounts of data, including sensitive data. On the other hand, blockchain technology enables the development of secure decentralized systems and offers guarantees regarding data integrity, application logic integrity and service availability. Thus, the idea to explore the potential of employing Blockchain technology to solve some of the main security and privacy issues encountered in the IoT it seems promising. In this talk we will discuss the convergence of the two technologies, we will analyze use cases of blockchain in the IoT and the encountered difficulties therein, and we will discuss possible research directions towards enhancing the applicability of blockchain technology to the IoT domain.



Jump, Crawl, Attract, Propagate: Security Challenges in Emerging Communication Networks

Stefan Schmid
University of Vienna

Brief Bio
Stefan Schmid is a Professor at the Faculty of Computer Science, at University of Vienna, Austria. He obtained his diploma (MSc) in Computer Science at ETH Zurich in Switzerland (minor: micro/macro economics, internship: CERN) and did his PhD in the Distributed Computing Group led by Prof. Roger Wattenhofer, also at ETH Zurich. As a postdoc, he worked with Prof. Christian Scheideler at the Chair for Efficient Algorithms at the Technical University of Munich and at the Chair for Theory of Distributed Systems at the University of Paderborn, in Germany. From 2009 to 2015, Stefan Schmid was a senior research scientist at the Telekom Innovation Laboratories (T-Labs) and at TU Berlin in Germany (Internet Network Architectures group headed by Prof. Anja Feldmann). In 2013/14, he was an INP Visiting Professor at CNRS (LAAS), Toulouse, France, and in 2014, a Visiting Professor at Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium. From 2015 to 2017, Stefan Schmid was a (tenured) Associate Professor in the Distributed, Embedded and Intelligent Systems group at Aalborg University, Denmark, and continued working part-time at TU Berlin, Germany. Since 2015, he serves as the Editor of the Distributed Computing Column of the Bulletin of the European Association of Theoretical Computer Science (BEATCS), since 2016 as Associate Editor of IEEE Transactions on Network and Service Management (TNSM), and since 2019 as Editor of IEEE/ACM Transactions on Networking (ToN). Stefan Schmid received the IEEE Communications Society ITC Early Career Award 2016. His research interests revolve around the fundamental and algorithmic problems of networked and distributed systems.

Communication networks have become a critical infrastructure of our digital society. But how much can we trust our networks today?
Over the last years, we have witnessed the emergence of interesting new kinds of networks. For example, programmable and virtualized networks introduced unprecedented operational flexibilities in datacenter and wide-area networks. Another example are payment channel networks which are considered a promising solution to the scalability problems of cryptocurrencies such as Bitcoin.
In this talk, I will provide an overview of the novel opportunities and challenges of emerging networking paradigms, in terms of security. In particular, I will show how such networks can increase the attack surface, enabling new attacks such as teleportation, tuple space explosion, exfiltration or denial-of-service on payments. I will then also discuss first ideas for solutions, from efficient isolation mechanisms, algorithmic networking monitoring, to machine learning.



Backdooring Deep Learning Architectures: Threats and (some) Opportunities

Mauro Barni
Università di Siena

Brief Bio
Mauro Barni graduated in electronic engineering at the University of Florence in 1991. He received the PhD in Informatics and Telecommunications in October 1995. He has carried out his research activity for almost 20 years first at the Department of Electronics and Telecommunication of the University of Florence, then at the Department of Information Engineering and Mathematical Sciences of the University of Siena where he works as associate Professor. During the last decade, his activity has focused on digital image processing and information security, with particular reference to the application of image processing techniques to copyright protection (digital watermarking) and authentication of multimedia (multimedia forensics). Lately he has been studying the possibility of processing signals that has been previously encrypted without decrypting them (signal processing in the encrypted domain – s.p.e.d.).
He is author/co-author of about 270 papers published in international journals and conference proceedings, he holds three patents in the field of digital watermarking and one patent dealing with anticounterfeiting technology. His papers on digital watermarking have significantly contributed to the development of such a theory in the last decade as it is demonstrated by the large number of citations some of these papers have received. The overall citation record of M. Barni amounts to an h-number of 42 according to Scholar Google search engine. He is co-author of the book “Watermarking Systems Engineering: Enabling Digital Assets Security and other Applications”, published by Dekker Inc. in February 2004. He is editor of the book “Document and Image Compression” published by CRC-Press in 2006.
He has been the chairman of the IEEE Multimedia Signal Processing Workshop held in Siena in 2004, and the chairman of the IV edition of the International Workshop on Digital Watermarking. He was the technical program chairman of the 2005 edition of the Information Hiding Workshop, the VIII edition of the International Workshop on Digital Watermarking and the V edition of the IEEE Workshop on Information Forensics and Security (WIFS 2013). He is the technical program co-chair of ICASSP 2014, to be held in Florence. In 2008, he was the recipient of the IEEE Signal Processing Magazine best column award. In 2010 he was awarded the IEEE Transactions on Geoscience and Remote Sensing best paper award.
He was the founding editor in chief of the EURASIP Journal on Information Security. He is part of the editorial board of the IEEE Signal Processing Magazine. He has served for 9 years as associate editor of the IEEE Trans. on Circuits and system for Video Technology and for 3 years the IEEE Transactions on Information Forensics and Security. In the past he served as associate editor of the IEEE Signal Processing Magazine (column and forum section), the IEEE Signal Processing Letters, the IEEE Transactions on Multimedia, the Eurasip Journal of Applied Signal Processing and the IET Proceedings on Information Security.
From 2010 to 2011, Prof. Barni has been the chairman of the IEEE Information Forensic and Security Technical Committee (IFS-TC) of the IEEE Signal Processing Society. He has been a member of the IEEE Multimedia Signal Processing technical committee and of the conference board of the IEEE Signal Processing Society. Mauro Barni is a fellow member of the IEEE and senior member of EURASIP. He was appointed distinguished lecturer by the IEEE Signal Processing Society for the years 2013-2014.
He participated to several National and European research projects on diverse topics, including digital watermarking, information security, signal processing in the encrypted domain and multimedia forensics. He is currently leading the VIPP (Visual Information Processing and Protection) group of the Telecommunication Laboratory of the Information Engineering Department at the University of Siena (http://clem.dii.unisi.it/~vipp/). The group currently consists of 7-10 members including faculty members, graduate and undergraduate students.

Decisions made by Deep Learning (DL) architectures are largely opaque to humans, making it difficult to verify if they behave as intended. A remarkable, security-oriented, problem induced by the opacity of DL networks, and by the necessity of training them on huge amounts of data, is the possibility that during the training phase an attacker, or the trainer itself, induces the network to misbehave as an answer to properly crafted inputs. In other words, the training process is corrupted in such a way to inject into the network a backdoor that the attacker can exploit at test time. Due to the opacity of DL, once a network has been trained it is very difficult to detect the presence of backdoors. In this framework, the goal of this talk is to introduce the basic means whereby backdoors can be created during training and activated at test time, the main threat models describing the security risks posed by backdoors and outline some possible approaches to detect the presence of backdoors, or at least to determine if the training data has been modified malevolently. We conclude the talk by drawing a parallelism between backdoors and watermarking, presenting a possible benevolent application of backdoors.