BIO: Elisa Bertino is professor of computer science at Purdue University, and serves as Director of the CyberSpace Security Lab (Cyber2SLab). She is also an adjunct professor of Computer Science & Info tech at RMIT in Melbourne. Prior to joining Purdue in 2004, she was a professor and department head at the Department of Computer Science and Communication of the University of Milan. She has been a visiting researcher at the IBM Research Laboratory (now Almaden) in San Jose, at the Microelectronics and Computer Technology Corporation, at Rutgers University, at Telcordia Technologies. Her recent research focuses on database security, digital identity management, policy systems, and security for web services. She is a Fellow of ACM, of IEEE, and AAAS. She received the IEEE Computer Society 2002 Technical Achievement Award, the IEEE Computer Society 2005 Kanai Award, and the ACM SIGSAC Outstanding Contributions Award. She is currently serving as EiC of IEEE Transactions on Dependable and Secure Computing.

Title: Security for the Internet of Things
Abstract: The Internet of Things (IoT) paradigm refers to the network of physical objects or "things" embedded with electronics, software, sensors, and connectivity to enable objects to exchange data with servers, centralized systems, and/or other connected devices based on a variety of communication infrastructures. IoT makes it possible to sense and control objects creating opportunities for more direct integration between the physical world and computer-based systems. IoT will usher automation in a large number of application domains, ranging from manufacturing and energy management (e.g. SmartGrid), to healthcare management and urban life (e.g. SmartCity). However, because of its fine-grained, continuous and pervasive data acquisition and control capabilities, IoT raises concerns about the security and privacy of data. Deploying existing data security solutions to IoT is not straightforward because of device heterogeneity, highly dynamic and possibly unprotected environments, and large scale. In this talk, after outlining key challenges in data security and privacy, we present initial approaches for profiling IoT devices with the goal of protecting them from being exploited by botnets.

BIO: Francisco Herrera (SM'15) received his M.Sc. in Mathematics in 1988 and Ph.D. in Mathematics in 1991, both from the University of Granada, Spain. He is currently a Professor in the Department of Computer Science and Artificial Intelligence at the University of Granada.

He has been the supervisor of 41 Ph.D. students. He has published more than 300 journal papers that have received more than 53000 citations (Scholar Google, H-index 115). He is coauthor of the books "Genetic Fuzzy Systems" (World Scientific, 2001) and "Data Preprocessing in Data Mining" (Springer, 2015), "The 2-tuple Linguistic Model. Computing with Words in Decision Making" (Springer, 2015), "Multilabel Classification. Problem analysis, metrics and techniques" (Springer, 2016), "Multiple Instance Learning. Foundations and Algorithms" (Springer, 2016).

He currently acts as Editor in Chief of the international journals "Information Fusion" (Elsevier) and “Progress in Artificial Intelligence (Springer). He acts as editorial member of a dozen of journals.

He received the following honors and awards: ECCAI Fellow 2009, IFSA Fellow 2013, 2010 Spanish National Award on Computer Science ARITMEL to the "Spanish Engineer on Computer Science", International Cajastur "Mamdani" Prize for Soft Computing (Fourth Edition, 2010), IEEE Transactions on Fuzzy System Outstanding 2008 and 2012 Paper Award (bestowed in 2011 and 2015 respectively), 2011 Lotfi A. Zadeh Prize Best paper Award of the International Fuzzy Systems Association, 2013 AEPIA Award to a scientific career in Artificial Intelligence, 2014 University of Jaen Award "Natural de Jaén", University of Granada Best paper Award Engineering Area (2011, 2013, 2014, 2015 and 2016), 2014 XV Andalucía Research Prize Maimónides and 2017 Andalucía Medal (by the regional government of Andalucía). He has been selected as a Highly Cited Researcher http://highlycited.com/ (in the fields of Computer Science and Engineering, respectively, 2014 to present, Clarivate Analytics)

Title : Quality data for quality decisions: Big data preprocessing with Spark
Abstract: Big Data applications are emerging during the last years, and researchers from many disciplines are aware of the high advantages related to the knowledge extraction from this type of problem.

The term of smart data is increasingly being used to refer to the challenge of transforming raw data into quality data that can be later processed to obtain valuable insights. To get quality data is the foundation for god data analytics. A big data practitioner must make data quality a priority to rely on data to take actions, make decisions, or predict outcomes.

Data preprocesssing is the knowledge extraction area including those tasks that transform the original data to hold the valuable data. Data preprocessing techniques adapt the data to fulfill the input demands of each data mining algorithm. Data preprocessing is an often neglected but major step in the data mining process. Data preprocessing includes data preparation methods for cleaning, transformation or managing imperfect data (missing values and noise data) and data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data, including feature and instance selection and discretization.

The design of data preprocessing methods for big data requires to redesign the methods adapting them to the new paradigms such as MapReduce and the directed acyclic graph model using Apache Spark. The main challenges are to deal with the increasing amount of data considering the number of instances and/or features, and the complexity of the problem.

In this talk we present the connection between big data and data preprocessing throughout all families of methods and big data technologies, including a short review of the state-of-the-art and a discussion on the research challenges.

BIO: Shiwen Mao [S'99-M'04-SM'09] received Ph.D. in electrical and computer engineering from Polytechnic University, Brooklyn, NY in 2004. He is the Samuel Ginn Distinguished Professor and Director of the Wireless Engineering Research and Education Center (WEREC) at Auburn University, Auburn, AL. His research interests include wireless networks and multimedia communications. He is a Distinguished Lecturer of the IEEE Vehicular Technology Society (VTS) for 2014-2018. He is on the Editorial Board of IEEE Transactions on Multimedia, IEEE Internet of Things Journal, IEEE Multimedia, ACM GetMobile, among others, and the Steering Committee of IEEE Transactions on Multimedia and IEEE Transactions on Network Science and Engineering. He is a TPC/Symposium Co-Chair of IEEE INFOCOM 2018, IEEE ICC 2017, IEEE WCNC 2017, among others. He received the 2015 IEEE ComSoc TC-CSR Distinguished Service Award, the 2013 IEEE ComSoc MMTC Outstanding Leadership Award, and the NSF CAREER Award in 2010. He is a co-recipient of the Best Demo Award from IEEE SECON 2017, the Best Paper Awards from IEEE GLOBECOM 2016 & 2015, IEEE WCNC 2015, and IEEE ICC 2013, and the 2004 IEEE Communications Society Leonard G. Abraham Prize in the Field of Communications Systems.

Title : RF Sensing for Vital Sign Measurement in healthcare Internet of Things
Abstract: Vital signs, such as breathing and heartbeat, are useful to health monitoring since such signals provide important clues of medical conditions. Effective solutions are needed to provide contact-free, easy deployment, low-cost, and long-term vital sign monitoring. Exploiting wireless signals for contact-free vital sign monitoring will be an important part of the future healthcare Internet of Things (IoT). In this talk, we present our recent work on contact-free vital sign monitoring. The first part is to exploit channel state information (CSI) phase difference data to monitor breathing and heartbeat with commodity WiFi devices. We will present PhaseBeat, a discrete wavelet transform based design, and TensorBeat, a tensor decomposition based design, as well as our experimental study to validate their performance. The second part of this talk is to exploit the CSI tensor and tensor decomposition to distinguish the respiration rates of multiple persons. In the last part of the talk, we will present our smartphone App based solution that uses a 20KHz ultrasound signal for breathing rate detection. Our experimental study shows that the proposed systems can achieve high accuracy under different environments for vital sign monitoring.

BIO: Anand R. Prasad, Dr. & ir. (MScEngg) from Delft University of Technology, The Netherlands, is Chief Advanced Technologist, Executive Specialist, at NEC Corporation, Japan, where he leads the mobile communications security activity. Anand is the chairman of 3GPP SA3, founder chairman of the GISFI Security & Privacy group and member of the governing body / council member of GISFI and TSDSI. He has 20+ years of experience in networking, wireless and mobile communications product design, development and business development in companies around the globe.

Anand has published 6 books and authored 50+ peer reviewed papers in international journals and conferences. Two of the books he co-authored on security are “Security in Next Generation Mobile Networks SAE/LTE and WiMAX”, published by River Publishers, and “Security for Mobile Networks and Platforms”, published by Artech House. He is a series editor for standardization book series and editor-in-chief of the “Journal of ICT Standardization” published by River Publishers.

He is recipient of the 2014 ITU-AJ “Encouragement Award: ICT Accomplishment Field” and the 2012 (ISC)² “Asia Pacific Information Security Leadership Achievements (ISLA) Award as a Senior Information Security Professional”. Anand is a certified information systems security professional (CISSP).

Title : 5G IoT Security: Future Revealed
Abstract: Internet of Things (IoT) will be integral part of 5G unlike other generations of mobile communications systems. In this talk we will discuss how 5G is expected to be and security associated to 5G as well as IoT. The talk will cover all aspects from radio to core and services to users. Focus of the talk will be on 3GPP based 5G security solution.

BIO: Dr Jinjun Chen is a Professor from Swinburne University of Technology, Australia. He is Deputy Director of Swinburne Data Science Research Institute, and Director of Data Science Platforms and Systems. He holds a PhD in Information Technology from Swinburne University of Technology, Australia. His research interests include scalability, big data, data science, software systems, cloud computing, data privacy and security, and related various research topics. His research results have been published in more than 140 papers in international journals and conferences, including various IEEE/ACM Transactions.

He received UTS Vice-Chancellor's Awards for Research Excellence Highly Commended (2014), UTS Vice-Chancellor's Awards for Research Excellence Finalist (2013), Swinburne Vice-Chancellor’s Research Award (ECR) (2008), IEEE Computer Society Outstanding Leadership Award (2008-2009) and (2010-2011), IEEE Computer Society Service Award (2007), Swinburne Faculty of ICT Research Thesis Excellence Award (2007). He is an Associate Editor for ACM Computing Surveys, IEEE Transactions on Big Data, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Cloud Computing, as well as other journals such as Journal of Computer and System Sciences, JNCA. He is the Chair of IEEE Computer Society’s Technical Committee on Scalable Computing (TCSC).

Title : Big Data - Big Application
Abstract: Right now, Big Data, Data Science or Data Analytics are being on wide interest in industry and academia. During this talk, we will discuss two questions based on my research industry engagement practice.

The first one is business gain from such buzz words. This is a practical question from business. Based on my research, big data can help business to identify big niche market opportunity which can grow up to become major markets. For example, by analysing and generalising potential weak connection between previously sparse data sources such as flight booking data and supermarket user data, we can better expand or enhance the market for personal recommendation on flight booking.

The second is about how researchers can make a full potential to business. A say is "It's not who has the best algorithm that wins. It's who has the most data" by Andrew Ng (Coursea founder). Data is becoming an important resource equally important to oil. While various public datasets are available to academics or researchers for research evaluation, those datasets may not be suitable or useful and timely for researchers. One way to make full potential of big data is to intensively work with industry because they have timely data. More or less, every industry is doing data analysis yet just on their specific purposes. We will brief our research and collaboration with specific industries.

BIO: Tatu Ylonen is a cybersecurity pioneer with over 20 years of experience from the field. He invented SSH (Secure Shell), which is the plumbing used to manage most networks, servers, and data centers and implement automation for cost-effective systems management and file transfers. He is has also written several IETF standards, was the principal author of NIST IR 7966, and holds over 30 US patents - including some on the most widely used technologies in reliable telecommunications networks.

He takes a broad view on cybersecurity and its implications for business and society. At the same time, he still loves to code and can descend through all the layers from process to protocols, operating system internals, assembly, and hardware. He has also founded a NASDAQ OMX-listed security company (SSH Communications Security) and held various leadership roles in a public company (including CEO, CTO, and Chairman). Nowadays he focuses on advancing cybersecurity and permanently solving some of its biggest hurdles. Building better dams instead of just fixing new leaks.

Title : Lessons on How Hackers Really Break into Systems
Abstract: The talk explores lessons learned on how hackers really break into information systems, from broad Internet-based attacks to highly sophisticated attacks used by government-sponsored attackers. It looks at hardware, firmware, operating system, application, cryptographic, and operational vulnerabilities over the years, and how hackers circumvented designed-in security or exploited omissions. It looks at the history of SSH (Secure Shell) as a case study, and looks at how vulnerable some organizations today are because of operational issues around it. Finally, the talk seeks to provide concrete guidance for the R&D community on how to bring a lasting improvement in security.

Slides of the keynote.

BIO: Lauri Oksanen is Vice President for Research and Technology in Nokia. He heads Technology, Architecture, Vision, and Standardization in Nokia Bell Labs. He started his industrial career 28 years ago in fiber optics in Nokia. Then Lauri moved to mobile networks where he has worked with all major wireless technologies from GSM to 5G. Lauri has worked in various advanced technology management positions covering fixed and wireless access, core, management and services, including also the HW and SW platforms and cloud and security technologies. Lauri has Master's and Licentiate degrees in Telecommunications from Helsinki University of Technology (now Aalto), where he also worked as a researcher before joining Nokia.

Title: Security in 5G era
Abstract: 5G will support a large range of new use cases. Many of those use cases are early in their evolution and their full impact regarding network security is today unclear. The network and the connections between people, devices and machines will be highly dynamic. Communication networks need to be able to react fast, flexibly, and reliably to new security situations, new attack vectors and upcoming technologies. Security needs to be automated to cope with the growth of data traffic and number of connections. Trust, a very human concept, needs to be digitalized to support the future use cases. Trust and security are not only a fundamental requirement from the user, but also a legal obligation to establish many of the new 5G use cases. The automation of security using machine learning to protect networks and the digitalization of trust in a virtual and highly dynamic network environment will be the focus of this presentation.