With the intriguing development of technologies in several industries along with the advent of accrescent and ubiquitous computational resources, it creates an ample number of opportunities to develop innovative intelligence technologies in order to solve the wide range of uncertainties, imprecision, and vagueness issues in various real-life problems. Hybridizing modern computational intelligence with traditional computing methods has attracted researchers and academicians to focus on developing innovative AI techniques using data science. International Conference on Data Science and Artificial Intelligence (ICDSAI) 2022, organized on April 23-24, 2022 by the Indian Institute of Technology, Patna at NITIE Mumbai (India) in collaboration with the International Association of Academicians (IAASSE) USA collected scientific and technical contributions with respect to models, tools, technologies, and applications in the field of modern Artificial Intelligence and Data Science, covering the entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations.
Sky Detection in Outdoor Spaces (S. Rajguru).- Defining, Measuring and
Utilizing Students Learning in a course (T. Garg).- Holistic Features and
Deep Guided Depth Induced Mutual Attention based Complex Salient Object
Detection (R. Singh).- Machine Learning based Decision Support System for
Resilient Supplier Selection (A. Dixit).- An Adaptive Task Offloading
Framework for Mobile Edge Computing Environment: Towards Achieving Seamless
Energy-Efficient Processing (M. Rasool).- Road Surface Classification and
Obstacle Detection for Visually Impaired People (S. Shilaskar).- A Survey on
Semantic Segmentation Models for Underwater Images (S. K. Anand).- An
Interactive dashboard for Intrusion Detection in Internet of Things (M.
Vishwakarma).- An Analous Review of the Challenges and Endeavor in Suspense
Story Generation Technique (V. Kowsalya).- Friend recommendation using
transfer learning in the autoencoder (A. Karande).- Analysis on the Efficacy
of ANN on Small Imbalanced Datasets(B. Shah).- Lightweight and Homomorphic
Security Protocols for IoT (I. Singh).- Tool based approach on Digital
Vulnerability Management Hub using The-Hive Platform (S. R. Babu).-
Performance Analyzer for Blue Chip Companies (I. Badole).- Strengthening Deep
Learning Based Malware Detection Models Against Adversarial Attacks (R.
Pai).- Video-based Micro Expressions Recognition using Deep Learning and
Transfer Learning (S. Kapadia).- Trustworthiness of COVID-19 News and
Guidelines (S. Singh).- Detection of moving object using modified fuzzy C-
means clustering from the complex and Non-Stationary background scenes (R.
Sangle) .- Deterrence Pointer for Distributed Denial of Service (DDoS)
attacks by utilizing Watchdog Timer and Hybrid Routing Protocol (S. J.
Kumar).- Modelling Logistic Regression and Neural Network for Stock Selection
With BSE 500 - A Comparative Study (S. Simon).- Landslide Detection with
Ensemble-of-Deep Learning-Classifiers trained with Optimal Features(A.
Kumar).- A Survey Paper on Text Analytics Methods for Classifying Tweets (C.
Agrawal).- A Survey on Threat Intelligence Techniques for Constructing,
Detecting, and Reacting to Advanced Intrusion Campaigns (A. Anand).-
Generalizing a secure framework for Domain Transfer Network for Face
antispoofing (A. Rana).- Survey on Game Theory Based Security Framework for
IoT (P. Joshi).- Intrusion Detection for IoT (S. L. Poojitha).-
Human-in-the-loop control and security for intelligent Cyber-Physical Systems
(CPS) and IoT (S. Sundarrajan).- Survey: Neural Network authentication and
tampering detection (P. Ashwin).- Misinformation Detection through
Authentication of Content Creators (K. K. Sudhama).- End-to-end network
slicing for 5G and beyond communications (R. K. Gupta).- Transparency in
Content and Source Moderation (A. R. Chandrassery).- A New Chaotic-Based
Analysis of Data Encryption and Decryption (Md M. Rahman).- Trust and
Identity Management in IOT (A. Tony).- Plant Pests Detection a Deep Learning
Approach (N. More).- S.A.R.A (Smart AI Refrigerator Assistant) (S. Kirkire).-
A Location Based Cryptographic Suite For Underwater Acoustic Networks (V. S.
Katasani).
Rajiv Misra is an Associate Professor of Computer Science and Engineering at the Indian Institute of Technology Patna, India. His research focuses in distributed systems, cloud computing, big data computing, consensus in blockchain, cloud IoT-edge computing, ad hoc networks, and sensor networks. He has contributed significantly to these research areas of distributed and cloud computing and published more than 80 papers in reputed journals and conferences, with an impact of 999 citations and an h-index of 14. Muttukrishnan Rajarajan is currently the Director of the Institute for Cyber Security at City University of London and carries out research in the areas of privacy preserving data management, Internet of Things privacy, network intrusion detection, cloud security and identity management using blockchain. Raj has received funding from EPSRC, Royal Academy of Engineering, European Commission, Innovate UK, British Council and industry tocarry out research in cyber security. He has supervised several PhDs jointly with British Telecommunications, UK in the area if data analytics for cyber security and network intrusion detection. Bharadwaj Veeravalli is currently with the Department of Electrical and Computer Engineering, Communications and Information Engineering (CIE) division, at The National University of Singapore, Singapore. His main stream research interests include cloud/grid/cluster computing(big data processing, analytics and resource allocation), scheduling in parallel and distributed systems, Cybersecurity, and multimedia computing. He is one of the earliest researchers in the field of Divisible Load Theory (DLT). He did PhD degree from the Indian Institute of Science, Bangalore, India. He received gold medals for his bachelor degree overall performance and for an outstanding PhD thesis (IISc, Bangalore India) in the years 1987 and 1994, respectively. Nishtha Kesswani has received prestigious awards, including the UGC Raman Postdoctoral Fellowship tenable in USA and the Young Teacher Award. She received the M.Tech. degree from the Malaviya National Institute of Technology (MNIT). She has a vivid teaching experience at several reputed universities, including California State University at San Bernardino and the University of Ljubljana, Slovenia. She has visited more than 15 countries and delivered invited talks at several conferences and workshops. She is currently with the Central University of Rajasthan, India. Ashok Patel has been a faculty member in the Department of Computer Science of Florida Polytechnic University, USA. He primarily teaches cybersecurity courses and is researching an improved efficient fingerprint recognition algorithm and web usage mining. He's particularly interested in personalizing the web experience for users and individuals using IOT. He has nearly 30years of teaching experience. Before immigrating to the United States, he was a professor in the Department of Computer Science of North Gujarat University in India. Imene Brigui holds a Ph. D. in Computer Science from the University of Paris-Dauphine. She is a specialist in Artificial Intelligence and more particularly in Multi-Agent Systems. She is particularly interested in the Design of Intelligent Systems for the automation of decision-making through preference learning and conflict management. The main areas of application of her research are E-commerce, Knowledge Management and Digital Learning. TN Singh is an alumnus of Banaras Hindu University (BHU) and has taught at the Department of Earth Sciences at the IIT Bombay. He received National Mineral Award in the year 2006 for his work. His research interest include Natural and Engineered Slope Stability, Rock Blasting, Rock Mechanics, Engineering Geology, Waste Dump and Rock Environment, Ground Control and CO2 Sequestration.
