This book presents the best-selected papers presented at the International Conference on Data Science, Computation and Security (IDSCS-2021), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, during April 16-17, 2021. The proceeding is targeting the current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing.

Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences - in this case, literally to the users' fingertips in the form of an iPhone app. About the Author Dr. Jesus Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.

This book discusses applications of blockchain in healthcare sector. The security of confidential and sensitive data is of utmost importance in healthcare industry. The introduction of blockchain methods in an effective manner will bring secure transactions in a peer-to-peer network. The book also covers gaps of the current available books/literature available for use cases of Distributed Ledger Technology (DLT) in healthcare. The information and applications discussed in the book are immensely helpful for researchers, database professionals, and practitioners. The book also discusses protocols, standards, and government regulations which are very useful for policymakers.

The two-volume set CCIS 1516 and 1517 constitutes thoroughly refereed short papers presented at the 28th International Conference on Neural Information Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. The 176 short and workshop papers presented in this volume were carefully reviewed and selected for publication out of 1093 submissions. The papers are organized in topical sections as follows: theory and algorithms; AI and cybersecurity; cognitive neurosciences; human centred computing; advances in deep and shallow machine learning algorithms for biomedical data and imaging; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; applications. * The conference was held virtually due to the COVID-19 pandemic.

This book constitutes revised and selected papers from the Sixteenth International Conference on Information Processing, ICInPro 2021, held in Bangaluru, India in October 2021. The 33 full and 9 short papers presented in this volume were carefully reviewed and selected from a total of 177 submissions. The papers are organized in the following thematic blocks: Computing & Network Security; Data Science; Intelligence & IoT.

The book first explores the cybersecurity's landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potential suspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law.

Security is the number one concern for businesses worldwide. The gold standard for attaining security is cryptography because it provides the most reliable tools for storing or transmitting digital information. Written by Niels Ferguson, lead cryptographer for Counterpane, Bruce Schneier's security company, and Bruce Schneier himself, this is the much anticipated follow-up book to Schneier's seminal encyclopedic reference, Applied Cryptography, Second Edition (0-471-11709-9), which has sold more than 150,000 copies.
Niels Ferguson (Amsterdam, Netherlands) is a cryptographic engineer and consultant at Counterpane Internet Security. He has extensive experience in the creation and design of security algorithms, protocols, and multinational security infrastructures. Previously, Ferguson was a cryptographer for DigiCash and CWI. At CWI he developed the first generation of off-line payment protocols. He has published numerous scientific papers.
Bruce Schneier (Minneapolis, MN) is Founder and Chief Technical Officer at Counterpane Internet Security, a managed-security monitoring company. He is also the author of Secrets and Lies: Digital Security in a Networked World (0-471-25311-1).

This book is designed to enable and encourage health professionals and family support workers to include fathers in the process of their work. It focuses on the enormous potential value of accessing men at a time they are known to be particularly receptive - before and after the birth - within the context of providing solutions in the debate about problematic aspects of masculinity and fatherhood. It looks at how important the father's role is within the family environment and how fathers should be encouraged to take part in the upbringing of their children.

This book presents a systematic study of practices and theories for query understanding of search engines. These studies can be categorized into three major classes. The first class is to figure out what the searcher wants by extracting semantic meaning from the searcher's keywords, such as query classification, query tagging, and query intent understanding. The second class is to analyze search queries and then translate them into an enhanced query that can produce better search results, such as query spelling correction or query rewriting. The third class is to assist users in refining or suggesting queries in order to reduce users' search effort and satisfy their information needs, such as query auto-completion and query suggestion. Query understanding is a fundamental part of search engines. It is responsible to precisely infer the intent of the query formulated by the search user, to correct spelling errors in his/her query, to reformulate the query to capture its intent more accurately, and to guide the user in formulating a query with precise intent. The book will be invaluable to researchers and graduate students in computer or information science and specializing in information retrieval or web-based systems, as well as to researchers and programmers working on the development or improvement of products related to search engines.

This book introduces the state-of-the-art algorithms for data and computation privacy. It mainly focuses on searchable symmetric encryption algorithms and privacy preserving multi-party computation algorithms. This book also introduces algorithms for breaking privacy, and gives intuition on how to design algorithm to counter privacy attacks. Some well-designed differential privacy algorithms are also included in this book. Driven by lower cost, higher reliability, better performance, and faster deployment, data and computing services are increasingly outsourced to clouds. In this computing paradigm, one often has to store privacy sensitive data at parties, that cannot fully trust and perform privacy sensitive computation with parties that again cannot fully trust. For both scenarios, preserving data privacy and computation privacy is extremely important. After the Facebook-Cambridge Analytical data scandal and the implementation of the General Data Protection Regulation by European Union, users are becoming more privacy aware and more concerned with their privacy in this digital world. This book targets database engineers, cloud computing engineers and researchers working in this field. Advanced-level students studying computer science and electrical engineering will also find this book useful as a reference or secondary text.

This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.

This book constitutes the thoroughly refereed post conference papers of the Third International Conference on Blockchain and Trustworthy Systems, Blocksys 2021, held in Guangzhou, China, in August 2021.*The 38 full papers and the 12 short papers were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections: Contents Blockchain and Data Mining; Performance Optimization of Blockchain; Blockchain Security and Privacy; Theories and Algorithms for Blockchain; Blockchain and Internet of Things; Blockchain and Smart Contracts; Blockchain Services and Applications; Trustworthy System Development.*

An insight into the biometric industry and the steps for successful deployment
Biometrics technologies verify identity through characteristics such as fingerprints, voices, and faces. By providing increased security and convenience, biometrics have begun to see widespread deployment in network, e-commerce, and retail applications. This book provides in-depth analysis of biometrics as a solution for authenticating employees and customers. Leading authority, Samir Nanavati explores privacy, security, accuracy, system design, user perceptions, and lessons learned in biometric deployments. He also assesses the real-world strengths and weaknesses of leading biometric technologies: finger-scan, iris-scan, facial-scan, voice-scan, and signature-scan. This accessible book is a necessary step in understanding and implementing biometrics.
Demystifies the complex world of optical networks for IT and business managers
Over the past few years, the cost of fiber optic networking has decreased, making it the best solution for providing virtually unlimited bandwidth for corporate LANs and WANs, metropolitan networks, Internet access, and broadband to the home. The only strategic book on optical networking technologies written from a real-world business perspective, Optical Networking demystifies complex fiber technologies for managers, and details the practical business benefits an optical network can offer. Debra Cameron explores established and emerging markets for optical networks as well as the enabling technologies, applications, network architectures, key deployment issues, and cost considerations. She also provides in-depth case studies of optical networks now in use in the United States and abroad.

This book constitutes the refereed post-conference proceedings of the 17th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2020, held in Rapperswil, Switzerland, in July 2020. The conference was held virtually due to the COVID-19 crisis. The 60 revised full papers presented together with 2 technical industrial papers were carefully reviewed and selected from 80 submissions. The papers are organized in the following topical sections: smart factory; digital twins; Internet of Things (IoT, IIoT); analytics in the order fulfillment process; ontologies for interoperability; tools to support early design phases; new product development; business models; circular economy; maturity implementation and adoption; model based systems engineering; artificial intelligence in CAx, MBE, and PLM; building information modelling; and industrial technical contributions.

This book establishes constructivist, interpretivist, and linguistic approaches based on conventions about the nature of qualitative and text data, the author's influence on text interpretation, and the validity checks used to justify text interpretations. Vast quantities of text and qualitative data in organizations often go unexplored. Text analytics outlined in this book allow readers to understand the process of converting unstructured text data into meaningful data for analysis in order to measure employee opinions, feedback, and reviews through sentiment analysis to support fact-based decision making. The methods involve using NVivo and RapidMiner software to perform lexical analysis, categorization, clustering, pattern recognition, tagging, annotation, memo creation, information extraction, association analysis, and visualization. The methodological approach in the book uses innovation theory as a sensitizing concept to lay the foundation for the analysis of research data, suggesting approaches for empirical exploration of organizational learning, knowledge management, and innovation practices amongst geographically dispersed individuals and team members. Based on data obtained from a private educational organization that has offices dispersed across Asia through focus group discussions and interviews on these topics, the author highlights the need for integrating organizational learning, knowledge management, and innovation to improve organizational performance, exploring perspectives on collective relationships and networks, organizational characteristics and structures, and tacit and overt values which influence such innovation initiatives. In the process, the author puts forward a new theory which is built on three themes: relationship and networks, knowledge sharing mechanisms, and the role of social cognitive schema that facilitate emergent learning, knowledge management, and innovation.

Business Process Management (BPM) has become one of the most widely used approaches for the design of modern organizational and information systems. The conscious treatment of business processes as significant corporate assets has facilitated substantial improvements in organizational performance but is also used to ensure the conformance of corporate activities. This Handbook presents in two volumes the contemporary body of knowledge as articulated by the world' s leading BPM thought leaders. This first volume focuses on arriving at a sound definition of BPM approaches and examines BPM methods and process-aware information systems. As such, it provides guidance for the integration of BPM into corporate methodologies and information systems. Each chapter has been contributed by leading international experts. Selected case studies complement their views and lead to a summary of BPM expertise that is unique in its coverage of the most critical success factors of BPM.

The second edition of this handbook has been significantly revised and extended. Each chapter has been updated to reflect the most current developments. This includes in particular new technologies such as in-memory data and process management, social media and networks. A further focus of this revised and extended edition is on the actual deployment of the proposed theoretical concepts. This volume includes a number of entire new chapters from some of the world's leading experts in the domain of BPM.

"

This book constitutes the refereed post-conference proceedings of the Third IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2020, held in Chennai, India, in February 2020.The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: computational intelligence for text analysis; computational intelligence for image and video analysis; and data science.

At the heart of modern cryptographic algorithms lies computational number theory. Whether you're encrypting or decrypting ciphers, a solid background in number theory is essential for success. Written by a number theorist and practicing cryptographer, Cryptanalysis of Number Theoretic Ciphers takes you from basic number theory to the inner workings of ciphers and protocols.

First, the book provides the mathematical background needed in cryptography as well as definitions and simple examples from cryptography. It includes summaries of elementary number theory and group theory, as well as common methods of finding or constructing large random primes, factoring large integers, and computing discrete logarithms. Next, it describes a selection of cryptographic algorithms, most of which use number theory. Finally the book presents methods of attack on the cryptographic algorithms and assesses their effectiveness. For each attack method the author lists the systems it applies to and tells how they may be broken with it.

Computational number theorists are some of the most successful cryptanalysts against public key systems. Cryptanalysis of Number Theoretic Ciphers builds a solid foundation in number theory and shows you how to apply it not only when breaking ciphers, but also when designing ones that are difficult to break.

In The United States of Anonymous, Jeff Kosseff explores how the right to anonymity has shaped American values, politics, business, security, and discourse, particularly as technology has enabled people to separate their identities from their communications. Legal and political debates surrounding online privacy often focus on the Fourth Amendment's protection against unreasonable searches and seizures, overlooking the history and future of an equally powerful privacy right: the First Amendment's protection of anonymity. The United States of Anonymous features extensive and engaging interviews with people involved in the highest profile anonymity cases, as well as with those who have benefited from, and been harmed by, anonymous communications. Through these interviews, Kosseff explores how courts have protected anonymity for decades and, likewise, how law and technology have allowed individuals to control how much, if any, identifying information is associated with their communications. From blocking laws that prevent Ku Klux Klan members from wearing masks to restraining Alabama officials from forcing the NAACP to disclose its membership lists, and to refusing companies' requests to unmask online critics, courts have recognized that anonymity is a vital part of our free speech protections. The United States of Anonymous weighs the tradeoffs between the right to hide identity and the harms of anonymity, concluding that we must maintain a strong, if not absolute, right to anonymous speech.

One of the "six best books for data geeks" - Financial Times With over 200 images and extensive how-to and how-not-to examples, this new edition has everything students and scholars need to understand and create effective data visualisations. Combining 'how to think' instruction with a 'how to produce' mentality, this book takes readers step-by-step through analysing, designing, and curating information into useful, impactful tools of communication. With this book and its extensive collection of online support, readers can: Decide what visualisations work best for their data and their audience using the chart gallery See data visualisation in action and learn the tools to try it themselves Follow online checklists, tutorials, and exercises to build skills and confidence Get advice from the UK's leading data visualisation trainer on everything from getting started to honing the craft.

This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technology, life support systems, fast detection, diagnoses, developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, solutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic.

This book paves the road for researchers from various areas of engineering working in the realm of smart cities to discuss the intersections in these areas when it comes to infrastructure and its flexibility. The authors lay out models, algorithms and frameworks related to the 'smartness' in the future smart cities. In particular, manufacturing firms, electric generation, transmission and distribution utilities, hardware and software computer companies, automation and control manufacturing firms, and other industries will be able to use this book to enhance their energy operations, improve their comfort and privacy, as well as to increase the benefit from the electrical system. The book pertains to researchers, professionals, and R&D in an array of industries.

This handbook covers recent advances in the integration of three areas, namely, cloud computing, cyber-physical systems, and the Internet of things which is expected to have a tremendous impact on our daily lives. It contains a total of thirteen peer-reviewed and edited chapters. This book covers topics such as context-aware cyber-physical systems, sustainable cloud computing, fog computing, and cloud monitoring; both the theoretical and practical aspects belonging to these topics are discussed. All the chapters also discuss open research challenges in the areas mentioned above. Finally, the handbook presents three use cases regarding healthcare, smart buildings and disaster management to assist the audience in understanding how to develop next-generation IoT- and cloud-enabled cyber-physical systems. This timely handbook is edited for students, researchers, as well as professionals who are interested in the rapidly growing fields of cloud computing, cyber-physical systems, and the Internet of things.

This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.

This book constitutes the refereed proceedings of the 14th IFIP TC 9 International Conference on Human Choice and Computers, HCC14 2020, which was supposed take place in Tokyo, Japan, in September 2020, but the conference was cancelled due to the COVID-19 crisis.The 31 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers deal with the constantly evolving intimate relationship between humans and technology. They are organized in the following sections: ethical and legal considerations in a data-driven society; the data-driven society; peace and war; our digital lives; individuals in data-driven society; and gender, diversity and ICT.