All delegates should bring the printout of the Order issued by Explara (refer to the email received from Explara during registration) and photocopy of valid ID Cards. The registration will be closed at 12.30 pm on all three days.

The QR Code will be scanned to issue the registration kit.

Abstract: We begin with developments that led to virtualization, network function virtualization, and disaggregation. How software-defined networking definition has changed due to disaggregation. The trend of DevOps and the slowness of the standardization activities has led the networking industry towards open source software and hardware. Open-sourcing has now become the fastest way to introduce new research, idea, concept or technology. All these trends and their impact on networking research along several related myths and issues will be discussed in this talk.

Abstract: Research in medical informatics is multifaceted, and has a wide scope of addressing any issue related to computing and technological advancement in healthcare and medicine. A specialized domain of this area is medical image processing primarily dealing with image-based studies, whereas medical imaging further narrows down the scope to noninvasive studies of anatomy and physiology of living beings. Nevertheless, there are generic issues and challenges while doing research in these areas. In this talk, we would consider them from a holistic viewpoint through a few case studies.

Abstract: How can we anticipate the evolving relationships between Fog Computing and the Internet of Things, Big Data and AI and the impact on our traditions of security and privacy? Computing in the Fog and at the Edge of the Internet of Things represents the greatest bilateral data exchange in the lives of others since the advent of the telephone. It may offer more than improved response times and reduced latency in home and personal data services. It may reintroduce user and community control over the data lives generated by remote systems introduced by the Internet of Things. At the same time, the invasive risks it presents to home and personal security and privacy may increase regulatory complexity to protect those rights. This tutorial invites you to map the technical, legal and social artifacts between these elements so we may:

Anticipate what may come and Identify design elements that may protect our needs in security and privacy

Abstract: This training is expected to cover foundations of Big Data, Why we need a different set of tools to analyze big data, Importance of Spark in analyzing Big Data, Use of Resilient Distributed Data Sets and Spark SQL. Further, there will be a demonstration of how to use pySpark for machine learning.

Outline

Introduction to Big Data Spark Architecture RDD in Spark Spark SQL & Dataframes Machine Learning with PySpark

Prerequisite The participants are expected to have python programming skills and basic understating of data analytics and machine learning

Software and hardware requirements for participants' laptops Laptops should be installed with MobaXterm (https://mobaxterm.mobatek.net/). There should not be any network issues with the laptop to connect with our main server.

-- NDN: New way of understanding Network ( Md Rashedur Rahman, Impress Capital Limited)
-- Prediction and Detection of Brain Tumors Using Machine Learning Techniques (Sudhanshu Suhas Gonge, Vishwakarma Institute of Technology, India)
-- Underwater communication and navigation (Mrinal Sarvagya, Reva University)
-- Neuro Fuzzy System for Epileptic EEG Signal Classification (Rajesh R, Central University of Kerala)
-- Real-world scenarios on Constraints of Digital Image Deep Processing (Sathya, MIT Anna University)
-- Interoperability of SDR Products (Abhay Shriramwar, Cyient Ltd)
-- A new secure Evidence Collection Protocol for Network Forensic Investigation (Rachana Yogesh Patil, A. C. Patil College of Engineering, Kharghar, Navi-Mumbai)
-- Security challenges In IoT Applications: An Authentication Approach (Patel Chintan J, Pandit Deendayal Petroleum University)
-- A New Polyalphabetic Substitution Scheme for Secure Communication (Ranju S Kartha, SNGCE, Kerala)
-- Federated Learning and its Applications, (Manu Vardhan, National Institute of Technology Raipur)

Abstract: This talk will cover historical and state-of-the-art developments in signal processing and machine learning techniques applied to biomedicine. Most of the real-world signals possess non-stationary and non-linear characteristics. Information processing and feature extraction from these signals is a challenging task. This talk will focus on five generations of signal processing algorithms developed for the analysis and interpretation of biomedical signals. The talk will touch upon event analysis, spectral analysis, time-frequency domain analysis, and multi-modal biomedical signal processing. Recent advances in using sparse signal representation and compressive sensing of long-term signals from wearables will also be covered. The application of the extraction and classification of features from cardiac signals, bio-acoustical signals, and sleep signals will be discussed in detail.

Posters:

Judy K George, Gayatri Menon B, Elizabeth Sherly, Visual Saliency Prediction Using Deep Model

Michael K, Asharaf S, Nikhil Chandran, Text-based Logical Question Answering

Renju V R, Malu G, Elizabeth Sherly, Diagnosis of Mild Cognitive Impairment Using Convolutional Neural Networks

Rudhra B, Elizabeth Sherly, Malu G, Diagnosis of Parkinson's Disease Using Deep Learning

Suma R, Anoop V.S., Asharaf S, Graph Convolutional Network for Cross-lingual Knowledge Graph Alignment

Nayana Uday, Elizabeth Sherly, Content-based Image Retrieval Using Convolutional Neural Network

Sreeshma Mohan, Indu V, Sabu M Thampi, A Cognitive Psychology Model for Limiting Bullying in Social Media

Sini S, Malu.G, tba

Abstract: This talk will present a personal perspective of a long-time researcher and some-time practitioner on cybersecurity trends and challenges. It will seek to draw some lessons from the decades-long history of this discipline, as well as from more recent developments. Finally, it will present some speculations on cybersecurity developments in the coming decade.

Abstract: Wireless Sensor Networks (WSNs) have been primarily introduced for defense applications, using large number of wireless sensor nodes (SNs) and a Base Station (BS) that collects information from all SNs. Secured communication in a WSN is an important aspect ignored by researchers and an innovative technique of distributing keys for shared secret key-based communication is described and various characteristics including resiliency are outlined. This presentation first introduces basics of sensor networks and the covers the problem of muscle fatigue which affects people from all walks of life. Muscle fatigue can be defined as a reversible decrease in the contractile strength of the muscle(s) that occurs after long lasting or repetitive muscular activity. Muscle fatigue, when not diagnosed and treated in the early stages, leads to muscle injuries which tend to have long-lasting effects. The current technologies which are used to detect and treat muscle fatigue are highly invasive and often require the personnel to visit specialized clinics. A non-invasive, cost-efficient method for detecting muscle fatigue is crucial. Infrared thermography is a non-radiating and contact-free technology which measures the surface temperature of objects. Infrared thermography can be an effective non-invasive technology which can be used to detect muscle fatigue. The thermal images of the test subjects are taken before and after the exercise routine. The changes in temperature values of the regions of interest have been tabulated and the results indicate a clear correlation between muscle fatigue and increase in the measured temperature. We conclude this talk with final remarks.

Abstract: Autonomous Vehicles (AVs) are incredibly disruptive and can be referred as the third transportation revolution. AVs will not only save commuting time and labour but also alleviate the need for huge parking lots, taxi services or even public transport. When AVs use electricity for fueling there will be a very positive impact on air pollution in as well. However, there are still many technical hurdles to overcome before fully realizing the benefits of AVs. In addition to machine learning and multi-sensor information fusion, V2X communication (where, X stand for Vehicle, Infrastructure or Network) is very essential for many safety aspects of AVs. 5G network-based RF solutions promise ultra-reliable low-latency connections for AV user cases via network slicing. On another frontier, Visible Light Communications (VLC) is gaining momentum to provide short-range V2X connectivity. Wide deployment of solid-state lights and, image sensors in vehicles enable simultaneous lighting, sensing and communication possibilities. The talk will highlight state of the art research issues in real time communication solutions for vehicular networks.

Abstract: "Social Engineering, in the context of information security, refers to psychological manipulation of people into performing actions or divulging confidential information." In other words, tricking the human mind to steal confidential information. A famous quote says ‘A chain is only as strong as its weakest link'. The weakest link in any security system is the ‘human being'. Recent trends show that most of the cyber-attacks begin with social engineering tactics. Phishing is one of the popular types of Social Engineering attacks. The valuable and sensitive information is captured via social engineering attacks and by using that information, the cybercriminals destroy the larger cyber ecosystem. Nowadays, financial frauds are using social engineering methods to steal bank related confidential information. The rate of these type of crimes also increased in recent years. There are a number of tools and techniques available to assist the social engineering attacks and it has became very easy for anyone to perform a social engineering attack. As these methods use the human mind exploitation, the technical controls to prevent those attacks are not much effective. However, there are various prevention mechanisms available in the cyber world. The banks are providing various options to protect their customers against money loss by financial frauds. A combination of technical controls and best practices would help to prevent the social engineering attacks to a great extent.

Abstract: Bayesian Optimization is a derivative free optimization approach for global optimization of an expensive black-box function and creates a surrogate model of the black-box objective function and finds the optimum of an unknown objective function from which samples can be obtained. It is a class of sequential-model based optimization algorithms that uses past evaluations of the function to find the next point to sample. Since the objective function is unknown, according to Bayesian theory the function is treated as random and a prior belief is placed over the function values, and as more values are observed, the posterior is updated based on the observation likelihood. These models use different types of acquisition functions to determine the next point to be evaluated based on the current posterior distribution over functions.
Outline including a short summary of every section:

1. First half- talk on Bayesian Optimization
   
   

An introduction to Optimization techniques, followed by an introduction and necessity of Bayesian Optimization to practical problems will be covered. In continuation, with an explanation of Gaussian Processes, several acquisition functions, the working of Bayesian Optimization will be covered and conclude with some practical applications of Bayesian optimization such as for astrophysics and automotive design.

2. Second half - Hands-on Bayesian Optimization (participants are expected to bring their laptops on Linux platform with Python 2.7 or its later version).

Hands-on Bayesian Optimization will be handled on the Python environment in which examples of the derivative-free optimization will be dealt with.

Length of the tutorial - 3 hrs

Policing Cyber Security in a Distributed World-A Role for Local Law Enforcement (Michael Losavio, University of Louisville)
A requisite for framing an optimum network structure (Anne Dickson, Mar Baselios College of Engg & Technology)
Deep Learning and Cancer (Sindhuja.M, Rajalakshmi Engineering College)
Mobile Phone-Based Drinking Water Nitrate Monitoring (Darsana S., College of Engineering, Chengannur)
U-COSFIRE lters for vessel tortuosity quantication with application to automated diagnosis of retinopathy of prematurity (Siva Kumar R, College of Engineering Trivandrum)
Security at Physical Layer in Wireless Network with Cooperative Jamming (Shashibhushan Sharma, National Institute of Technology, Durgapur)
Sociology, Models and Computing (Prakash Hegade, KLE Technological University, Hubballi)
Heart and Lung Sounds Analysis for Diagnostic Purpose ( Madhusudhan Mishra, North Eastern Regional Institute of Science and Technology, Arunachal Pradesh)
Communication using IoT Architecture in Marine Environment (P Karthik, K S School of Engineering and Management)
IoT based Cognitive Video Analytics for Crowd Anomaly Detection (Elizabeth B Varghese, IIITM-K)

Abstract: 5G technology is making rapid advances and introducing new challenges in mobile communications. Artificial Intelligence (AI) and Machine learning (ML) techniques are opening up new opportunities in the mobile communications area, as these techniques can be used to personalize user experience while reducing the cost of network deployment and maintenance.

In this talk, a brief introduction to the features of 5G wireless networks will be presented first in comparison to earlier versions like 3/4 G wireless networks. Key infrastructure aspects and enabling technologies driving the 5G revolution will then be discussed. Typical methods to develop AI/ML powered 5G networks which are context-aware and have cognitive abilities will be discussed along with a list of research issues in this exciting technology domain. A brief description of how state of the art techniques like AR/VR are driving 5G network limits will also be presented. The talk will conclude by providing pointers and insights to signal processing researchers on how they can contribute to this exciting area.

Abstract: High-performance computing (HPC) impacts every aspect of scientific endeavor. In this talk, I will cover various HPC problems and applications over four decades from my journey in academia and industry. These include new multi-(many) core processors and interconnection networks, parallelizing compilers for non-uniform dependences, OpenMP for heterogeneous processors, Virtual Machines for HPC, multi-threaded embedded operating systems, accelerating bioinformatics algorithms using FPGAs and GPUs, hyper-converged computer systems and variable redundancy for flash storage arrays, and machine learning. I will describe applications of HPC in surgery and medical diagnosis and the future challenges in HPC.

Abstract: Software-defined networking facilitates better network management by decoupling the data and control planes of legacy routers and switches and is widely adopted in the data center and production networks. The decoupling of control and data planes facilitates more optimal network management and deployment of elaborate security mechanisms but also introduces new vulnerabilities that could be exploited using distributed denial of service (DDoS) attacks. This talk presents several protocol vulnerabilities and resource limitations that are exploited by DDoS attacks. Often, techniques mitigate these attacks change the attack surface, which can lead to new vulnerabilities exploitable by new DDoS attacks. Several examples of new vulnerabilities introduced by DDoS mitigation schemes are presented with potential attacks to exploit them. The talk concludes with some guidelines on designing DDoS attack mitigation schemes that minimize the introduction of new vulnerabilities.

Abstract: Quantum cryptography is one of the most mature areas of quantum information. In the past few decades, active research took place towards standardizing quantum key distribution. This resulted in the hardening of theoretical proofs for a robust implementation against realistic attacks on QKD system which was executed by exploiting the security loopholes. On one hand, many hacking strategies of the source, link, and detection system have been demonstrated. This paved the way for the development of robust engineering QKD products. The emphasis of this paper is twofold, on one hand it brings forth the newer security techniques paving way for information-theoretic security proofs of comparatively newer QKD protocols leading to high QKD performance for market deployment, on the other hand, it discusses the recent quantum hacking on different QKD systems which have led to the strengthening of the QKD system and enabled active monitoring against possible eavesdropping activities.

Abstract: Controller Area Network (CAN) is a serial asynchronous communication protocol. It is the most widely used protocol in the automotive sector, mainly because of its robustness. Its error handling mechanism and fault confinement feature made it best suited for the vehicular communication between the ECU. Messaged based communication feature of CAN provides flexibility to connect ‘n' number of nodes to the network without any changes in the hardware. Since the address is not involved in the frame transmission, by default, it becomes broadcast kind of communication protocol. CAN bus is very less immune to noise because it has adopted the differential voltage concept. The protocol is supplemented with invaluable features that make the OEMs and suppliers of ECUs prefer the CAN protocol. The proposed workshop focuses on building CAN network using cortex- m3 and analyzing the CAN bus data using advanced automotive tools. The workshop covers the theoretical background of CAN protocol, operation, developing C-code for transmitting and receiving CAN Data and its applications in the automotive and other industries.

Abstract: An abstract model of any complex physical system gives rise to a complex network model. Networks obtained by modeling complex systems result in a complex interconnection of nodes (vertices) by edges (links or arcs). The study of complex networks, also known as network science, is important due to the fact that complex networks appear in many aspects of our life such as biological networks, molecular networks, social networks, transportation networks, electric power grids, communication networks, and the Internet. In fact, most physical and biological systems often behave as complex networks of subsystems and connectivities among them. Therefore, complex network modeling spans a large number of natural as well as man-made networks. Further, there has been an evolution of Big Data in the form of large scale networks arising from social networks, biological networks, computer networks, and the Internet. This tutorial is an effort toward understanding the networking aspect of complex networks and discuss the current state of research as well as the open research issues.

Title for the session: New Social Paradigms from New Technologies - How to Build Novel Models of Transdisciplinary Security, Integrity and Authenticity in the Messy Human World of the Information Polity. (December 20, 2019 15.15 - 16.15 )

Organizer(s):

-- Michael Losavio, University of Louisville, USA -- Svetlana Polyakova, Perm State University, Russian Federation -- Pavel Pastukov, Perm State University, Russian Federation -- Alec Yasinsac, Professor and Dean, University of South Alabama, USA

Brief topic description:

Dissatisfaction with information security in our world of pervasive computing has led to calls for new paradigms to secure the confidentiality, integrity and authenticity of often vital information. Some paradigms represent old-style authoritarian control of information, hindering benefits for education and enlightenment. Others transfer responsibility and autonomy to individuals themselves.

This session discusses ways technologies, law and political must come together to create a coherent, beneficial regime of information security. The IBM Skills Academy Design Thinking model guides our iterative solution session on what next to do.

Workshop Outline:

Introduction to Blockchain
History of Blockchain and Bitcoin Networks
Features of Blockchain
Cryptography in Blockchain
Consensus Protocols in Blockchain
Proof of Work
Bitcoin Mining
Ethereum Networks
Introduction to Smart Contracts & Remix IDE
Write your first smart contract using Solidity
Metamask Wallet

Workshop Page: http://coconet-conference.org/2019/?q=node/49