Tutorials

Event Date: Tuesday, 3rd January, 2023

Toward Automated Security Risk Assessment: Models, Metrics, and Recent Applications

Graphical security models such as attack graphs, attack trees, and other variants have been used for attack/threat modeling and analysis. This tutorial introduces how we can automate security risk analysis for given systems and networks. This will introduce the basic concepts of graphical security models, metrics, and their applications. The tutorial is organized as follows. It starts with an introduction to security modeling and analysis followed by the three fundamental terms/concepts such as graphical security models, measurement and metrics. The last part is focused on the recent advances in graphical security models and their applications in various application domains. The agenda will be: Introduction - Basic Concepts, Terminologies; Graphical security models, measure and metrics, and life cycle; Recent advances in graphical security models; and Graphical security models and their applications (Cloud computing, Moving Target Defense, IoT, etc).

Speaker: Dr Dan Dongseong Kim (University of Queensland, Australia)

Dr Dan Dongseong Kim is an Associate Professor in Cybersecurity at The University of Queensland, Australia since Jan 2019. Prior to UQ, he led the Cybersecurity Lab at the University of Canterbury (UC), Christchurch, New Zealand from August 2011 to December 2018. From June 2008 to July 2011, Dr Kim was a postdoc in Hudson Chaired Prof. Kishor S. Trivedi (IEEE fellow, the IEEE 2008 Technical Achievement Award recipient)’s research group at Duke University, North Carolina in the US. He worked on Metrics, Models, and Analysis of Network Security funded by the US NSF and Performability Analysis of Cloud Computing funded by the IBM T.J. Watson and NEC Japan, respectively. He was a visiting scholar in Prof. Virgil D. Gligor (currently with the Carnegie Mellon University in the US, former ACM SIGSAC chair, the IEEE 2013 Technical Achievement Award Recipient)’s Security research group at the University of Maryland, College Park, Maryland in the US in 2007. Dr. Kim’s research was supported by the NATO SPS programme, the New Zealand’s MBIE, the Qatar National Research Fund, the US Army Research Lab, and the Agency for Defense Development in South Korea. His research interests are in cybersecurity and privacy.

Identification of Causal Dependencies in Multivariate Time Series

Telecommunications networks operate on enormous amount of time-series data, and often exhibit anomalous trends in their behaviour. This is caused due to increased latency and reduced throughput in the network which inevitably leads to poor customer experience. One of the common problems in machine learning in the telecom domain is to predict anomalous behaviour ahead of time. Whilst this is a well-researched problem, there is far less work done in identifying causal structures from the temporal patterns of various Key Performance Indicators in the telecom network. The ability to identify causal structures from anomalous behaviours would allow more effective intervention and generalization of different environments and networks. The tutorial is focused on discussing existing frameworks for establishing causal discovery for time-series data sets. In this hands-on tutorial, we will be covering at least 3 state-of-the- art methods on causal time series analysis including Granger causality, convergent cross-mapping, Peter- Clark Momentary Conditional Independence and Temporal Causal discovery framework. The need for a causation analysis, beyond correlation will also be explained using publicly available datasets, such as, double pendulum dataset. The state-of-art methods are chosen to cover various aspects of the causal time series analysis, such as modelling the non-linearity, attempting the problem from chaos and dynamic systems (CCM), information-theoretic approaches (PC-MCI), or having a data-driven approach (TCDF). State-of- the-art survey papers show that none of the methods can be said to be ideal for all the possible time series and there are relative advantages and shortcomings for each of these methods.

Speakers: Sujoy Roychowdhury, Serene Banerjee, and Ranjani H.G. (Ericsson, India)

Sujoy Roychowdhury, Principal Data Scientist Ericsson R&D (GAIA) has over 15 years of experience in Machine learning and Artificial Intelligence. His main interests are in deep learning, causal reasoning and computer vision.
Serene Banerjee, Master Researcher, Ericsson Research, Bangalore, has 18+ years of industrial experience post completion of her Ph.D. from The Univ. of Texas at Austin, under Prof. Brian L. Evans in 2004. She has a B.Tech. (H) in Electronics and Electrical Communications Engineering from IIT Kharagpur in 1999. At Ericsson she is focusing on developing AI/ML algorithms for Radio Access Networks.

Ranjani, Principal Data Scientist Ericsson R&D (GAIA) has a total of 19 years experience combined in academia and industry. She completed her Ph.D. and M.Sc (Engg) from IISc, Bangalore. Her research interests include machine learning, signal processing, speech audio and music signal analysis, RAN. She has 4 filed patents, and more than 10 peer reviewed publications.

5G Architecture Overview, Software Stack and Use Cases

Mobile networks are seeing a dramatic evolution as they prepare for the transition to 5G and meet the demands of new 5G services like Massive IoT, enhanced mobile broadband, tactile internet, smart city, and virtual reality. The demands on the service provider network will increase multi-fold to support new 5G use cases capabilities such Enhanced mobile broadband (eMBB), Ultra reliable low latency communications (URLLC) and massive machine type communications (MMTC). These services require programmability in the network along with simpler architecture that can be scaled rapidly through automation. This detailed technical tutorial showcases the transformation journey of the IP networks as they transition to 5G through architecture, use cases, practical case-study, design best practices, software stack & automation.

Speakers: Atahar Khan, Satya Priyo Dhar, and Ramakrishnan Shanmugasundaram (Cisco, India)

Atahar is a Cisco Senior Solutions Architect with 17 plus years of designing, architecting, and deploying complex Service Provider networks technologies of Mobile Backhaul and its evolution into xHaul for 5G networking, SRMPLS/SRv6, and RON. Atahar holds CCIE SP and approved Cisco Patents in areas of 5G, SP technologies & AI/ML. In addition, he has published a whitepaper on seamless MPLS, Segment routing network design & migration, and network timing.
Satya is a Solutions Architect in Cisco with 17 plus years of work experience in Service Provider network technologies design, architecture, testing and deployment. Satya holds an active CCIE- 49679, passionate about technical tech talks, training workshops and events and is actively working with customers on their network transformation journey to converged SDN based programmable 5G network with Segment Routing ,EVPN and end to end automation.

Ramkakrishnan is a Cisco Solutions Architect with 17+ years of designing, architecting, and deploying complex Service Provider networks technologies of Mobile Backhaul networking, SR- MPLS/SRv6, and Manged SP. Ramki has Patents in areas of SP technologies & IOT.

Deep Learning based Radio Frequency Signal Classification: Hands-on

Radio Frequency (RF) signal classification is a key technique of Dynamic Spectrum Access (DSA) to utilize the unused spectrum in Cognitive Radio (CR) to meet the ever- increasing traffic demands for the next generation 5G and beyond cellular networks. In recent years, the RF signal classification for CR-based applications using Deep Learning (DL) architectures has received considerable attention. This tutorial focuses on a DL-based framework with Convolution Neural Network (CNN) architecture for classifying various modulation schemes such as BPSK, QPSK and GMSK. The real-time GSM signals captured from the nearby base stations will be used to analyze the performance of the developed CNN architecture.

Speakers: Prabhu Chandhar and Sathish Babu (Chandhar Research Lab, India)

Dr. Prabhu Chandhar, Director, Chandhar Research Labs, Chennai, India. Prabhu Chandhar received the Ph.D. degree from IIT Kharagpur, Kharagpur, India in 2015. From 2009 to 2010, he was a Senior Research Fellow at the Vodafone IIT KGP Centre of Excellence in Telecommunications, IIT Kharagpur. From 2015 to 2017, he was a Post-Doctoral Researcher at the Division of Communication Systems, Link¨oping University, Link¨oping, Sweden. Since 2018, he serves as the Director of Chandhar Research Labs, Chennai, India. His research interests are within the fields of Signal Processing and Communication Theory.

Dr. Sathish Babu, Senior Researcher, Chandhar Research Labs, Chennai, India. Sathish Babu received the Ph.D. degree from IIT Kharagpur in 2017. From 2010 to 2017, he worked as a Junior Project Officer handling sponsored research projects at Kalpana Chawla Space Technology Cell (KCSTC), IIT Kharagpur in collaboration with Indian Space Research Organization (ISRO) – Satellite Application Centre (SAC), Ahmedabad in the field of satellite Navigation. From 2017 to 2019, he was working as an Adhoc Faculty at National Institute of Technology Puduchery, Karaikal. Since 2020, he works as a senior researcher at Chandhar Research Labs Pvt. Ltd., Chennai. His research interests include Signal Processing and Communication for Next generation wireless systems, Machine Learning for RF; and Satellite Navigation.

5G Non-Terrestrial Networks: Recent Advancements, Open Challenges, and Research Tools

The integration of 5G with Non-Terrestrial Network (NTN) components is going through a series of technological advancements and soon satellites will be a part of the 5G ecosystem. The integration is also boosted-up by its formal standardization in the 3GPP Release-17 and further enhancements are planned for Release-18. Benefits of 5G-NTN are enormous and so are the challenges. This tutorial aims to educate the audience on the latest advancements in 5G Non-Terrestrial Networks (5G-NTN), the current status of research, implementation challenges, experimentation tools, and open research problems. The first part of the tutorial overviews the basics of 5G-NTN, potential use cases, different architectures, and their trade-offs. The first part also provides peculiar features of 5G New Radio (NR) and satellite communication for an in-depth understanding of the second and third parts of the tutorial. The second part addresses the standardization of NTN in the 5G ecosystem followed by the technical challenges posed by both the NTN channel and the 5G protocol stack. The third part of the tutorial focuses on the description of software and hardware research tools and details of ongoing/completed 5G-NTN projects. The third part of the tutorial also includes a few demonstrations using open-source software OpenAirInterface. Finally, the long-term outlook of 5G-NTN and open research topics are discussed.

Speakers: Sumit Kumar and Jorge Querol (University of Luxembourg, Luxembourg)

Sumit Kumar received the B.Tech in Electronics & Communication Engineering from Gurukula Kangri University, Haridwar, India (2008), M.S. in Wireless Communication and Signal Processing from International Institute of Information Technology, Hyderabad, India (2014), and a Ph.D. in Wireless Communication from Eurecom, France (2019). During his Master's, he worked on several projects funded by the Department of Science and Technology, India. His Ph.D. thesis was devoted to interference management and co-existence of wireless systems where architecture for a multi-standard SDR receiver was developed and demonstrated. In 2019, he joined the SIGCOM research group, Interdisciplinary Centre for Security, Reliability, and Trust (SnT) at the University of Luxembourg, Luxembourg as a Research Associate. He is involved in several European Space Agency (ESA) and Luxembourgish national projects related to 5G, 5G Non-Terrestrial Networks, EMF Radiation, and Satellite Communication. His research interests include Software Defined Radio, Interference Management, 5G, 5GNTN, and Computer Networking.

Jorge Querol was born in Forcall, Castell'o, Spain, in 1987. He received a B.Sc. degree in telecommunication engineering, an M.Sc. degree in electronics engineering, an M.Sc. degree in photonics, and a Ph.D. degree (cum laude) in signal processing and communications from the Universitat Polit`ecnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain, in 2011, 2012, 2013, and 2018, respectively. His Ph.D. thesis was devoted to the development of novel antijamming and counter-interference systems for global navigation satellite systems (GNSS), GNSS-reflectometry, and microwave radiometry. One of his outstanding achievements was the development of a real-time standalone pre-correlation mitigation system for GNSS, named FENIX, in a customized software-defined radio (SDR) platform. FENIX was patented, licensed, and commercialized by MITIC Solutions, a UPC spin-off company. In 2018, he joined the SIGCOM Research Group, Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Luxembourg as a Research Associate, and he was promoted to Research Scientist in 2021. He is also the head of the SatComLab/5G-SpaceLab. He is involved in several ESA and Luxembourgish national research projects dealing with signal processing and satellite and space communications, signal processing, and satellite navigation. His research interests include software-defined radios (SDR), real-time signal processing, satellite communications, 5G nonterrestrial networks, satellite navigation, and remote sensing. Dr. Querol received the Best Academic Record Award of the Year in Electronics Engineering at UPC in 2012, the First Prize of the European Satellite Navigation Competition (ESNC) Barcelona Challenge from the European GNSS Agency (GSA) in 2015, the Best Innovative Project of the Market Assessment Program (MAP) of the EADA Business School in 2016, the Award Isabel P. Trabal from Fundaci'o Caixa dEnginyers for its quality research during his Ph.D. in 2017, and the Best Ph.D. Thesis Award in remote sensing in Spain from the IEEE Geoscience and Remote Sensing (GRSS) Spanish Chapter in 2019.

Cloud-native Networking Deep Dive

Widespread adoption of container deployment for microservices has spurned a whole body of research in cloud-native networking. The interest is more profound with multi-cloud networking to support edge deployments. The tutorial aims to cover the cloud/ multi-cloud networking concepts with a hands-on experience.

Speakers: Chander Govindarajan and Priyanka Naik (IBM Research, India)

Chander is a Research Engineer at IBM Research, India with 5 years experience in the field of systems ranging from Blockchain, Telco-Cloud and Multi-Cloud Networking, working in the intersection of academic research and business interests. Prior to joining IBM Research, he completed his Dual-Degree in CSE from IIT Kharagpur.

Priyanka is a Research Scientist at IBM Research, India. Her area of interest lie in optimizing the deployment of containerized network functions. She is currently working on multi-cloud networking and its aspects around frameworks for edge and cloud connectivity. Prior to joining IBM she obtained her Ph.D. from IIT Bombay.

OTFS Aided Cell-free Massive MIMO for Beyond 5G

Fifth generation (5G) cellular communication uses massive multiple-input multiple-output (MIMO) technology to enable precise beamforming towards any location in the cell. Several countries have commercially deployed 5G systems with massive MIMO technology. Researchers have already started to look for beyond 5G technologies, with an aim to support the ever increasing demands for a wide range of network services, seamless growth in the number of wireless connected devices and to provide a better user experience. In this regard, many new technologies have emerged, such as ultra-massive multiple-input multiple-output (UM-MIMO), cell-free massive MIMO, reconfigurable intelligent surfaces, orthogonal time-frequency space (OTFS), among others, as a probable candidate for beyond 5G (B5G) communication systems.

Cell-free massive MIMO concept has been recently proposed as a promising technique for B5G systems, thanks to its capability to support a high density of network devices, while providing substantial improvement in connectivity, spectral and energy efficiencies. A cell-free massive MIMO system is a distributed architecture where a large number of geographically distributed access points (APs) serve a number of users distributed over a large area. Many aspects of cell-free systems are being actively researched, with a focus on technical foundations, resource allocation and signal processing and practical implementation. Nevertheless, high mobility scenarios, such as high-speed railways, vehicle to vehicle (V2V) communications, and unmanned aerial vehicles (UAV) communications have remained largely unexplored. These applications pose a significant challenge in designing cell-free technology for future wireless communication systems. High Doppler spread and multipath propagation observed in such applications result in a doubly dispersive channel, which significantly degrades its estimation and tracking.

Orthogonal frequency division multiplexing (OFDM) has been a dominant waveform for more than a decade. 4G-LTE and 5G-new radio (NR) technologies use OFDM waveform to overcome the effect of a frequency-selective wireless channel. However, the bit error rate (BER) of OFDM waveform, which multiplexes symbols in the time-frequency (TF) domain, deteriorates significantly over doubly dispersive channels. The recently-proposed orthogonal time-frequency space (OTFS) waveform, instead multiplexes symbols in the Delay-Doppler (DD) domain, and has been shown to achieve a significantly lower BER than OFDM over vehicular speeds ranging from 30 km/h to 500 km/h. OTFS waveform has recently been amalgamated with massive MIMO and cell free massive MIMO technologies for catering high mobility use cases for beyond 5G wireless systems. The topics to be covered in this tutorial are as follows.

Cell-free, small-cell and cellular networks: Understand the benefits of cell-free network when compared to small-cell and cellular network. Clearly point out with proper reasoning, at what condition either cell-free, small-cell or cellular network will perform better.

Cell-free massive MIMO system: Understand how user-centric massive MIMO system is different than conventional cell-free system. Analyse the downlink user-centric cell free massive MIMO system.

Cell-free massive MIMO channel properties: Analyse the impact of number of APs on channel hardening. Analyse the impact of geometric distribution of APs on channel hardening and favorable propagation.

Practical pulse-shaped MIMO-OTFS system model: Fundamentals of OTFS waveform for MIMO communication will be explained.

MIMO-OTFS channel properties: The inherent properties of MIMO-OTFS channel matrix, which can be exploited to reduce receiver complexity, will be explained.

Low-complexity receiver design for cell-free massive MIMO-OTFS: OTFS waveform, after interacting with a doubly dispersive channel, results in a twisted convolution, which radically increases receiver complexity. Consequently, this topic will cover low-complexity receiver design for cell-free massive OTFS systems.

Intended audience of the tutorial: Research scholars

Requirement for attendees: None

Speakers: Prem Singh (IIIT Bangalore) and Ekant Sharma (IIT Roorkee)

Prem Singh received M. Tech and PhD degrees in Electrical Engineering from the Indian Institute of Technology Kanpur, India, in 2011 and 2020 respectively. He worked as Project Executive Officer on the Indigenous 5G Testbed project, where he designed FPGA based hardware, and software algorithms for an end-to-end 3GPP compliant 5G-NR Testbed. His PhD thesis received the Best Thesis award in IEEE CICT 2020 organized by IIIT Kancheepuram, India, and was one of the finalists (top two) for the Indian National Academy of Engineering (INAE) Innovative Student Project Award 2021. His two recent research papers were picked by the IEEE Communication Society for the best readings for OTFS and Delay-Doppler signal processing. His student’s paper was one of the finalists for the best student paper award at the IEEE SPCOM, IISc Bangalore, India, July 2022. His current research interests lie in the area of parameter estimation and transceiver design for 5G and beyond wireless technologies including Orthogonal Time-Frequency space (OTFS), Filter Bank Multicarrier (FBMC), massive MIMO and Millimeter-wave. His interests also include designing practical 5G and beyond wireless systems using 3GPP standards. He is currently working as an assistant professor at IIIT Bangalore.

Ekant Sharma (Member, IEEE) received the M.Tech. and Ph.D. degrees in electrical engineering from the Signal Processing, Communication and Networks Group, Department of Electrical Engineering, Indian Institute of Technology Kanpur, India, in May 2011 and May 2020, respectively. From 2011 to 2012, he was with the IBM-Indian Software Laboratory and worked as an Associate Software Engineer. From August 2019 to January 2021, he worked with the 5G Testbed Laboratory, Indian Institute of Technology Kanpur, where he designed base station hardware and software algorithms for 5G NR. He is currently working as an Assistant Professor with the Indian Institute of Technology Roorkee. His Ph.D. thesis received outstanding thesis award and also it was chosen for category: SPCOM Best Doctoral Dissertation—Honourable Mention at IEEE SPCOM Conference. His research interests are within the areas of wireless communications systems, with special focus on practical massive MIMO, full-duplex, relays, and energy efficiency and optimization.

CFP for Tutorials

Download PDF of the CFP for Tutorials

The 15th International Conference on COMmunication Systems and NETworkS (COMSNETS) will be held in Bangalore, India, during January 3 - 8, 2023. For this premier international conference, we invite tutorials from experts in their fields. Tutorial topics should be within the scope of COMSNETS that includes, but is not limited to, advances in communication systems/networks, Internet of things, edge/cloud computing, applications of machine learning in communication systems/networks, and information security/privacy.

Tutorials should aim to educate the audience on emerging topics. Presenters can choose a suitable format for the tutorials, such as presentation or hands-on training. We encourage the tutorials to be interactive. The preferred duration of a tutorial should be 3 hours. We will also consider proposals for 6-hour tutorials.

Submissions:

Submission Link: https://edas.info/newPaper.php?c=29769

We solicit an abstract for the tutorial. The abstract should be at most 3 pages long. It should adhere to the same submission guidelines as those for a paper submission to the main conference. Abstracts that do not adhere to the guidelines will be rejected without review. The abstract must include the following: