Advances in Data Sciences, Security and Applications PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Advances in Data Sciences, Security and Applications PDF full book. Access full book title Advances in Data Sciences, Security and Applications by Vanita Jain. Download full books in PDF and EPUB format.
Author: Vanita Jain
Publisher: Springer Nature
ISBN: 9811503729
Category : Technology & Engineering
Languages : en
Pages : 466
Get Book
Book Description
This book gathers the best papers presented at the International Conference on Data Sciences, Security and Applications (ICDSSA 2019), organized by Bharati Vidyapeeth’s College of Engineering, New Delhi, India, on 7–8 March 2019. The respective contributions present original research work, essential information, techniques and applications in the fields of data mining, artificial intelligence and computational intelligence. They also discuss machine learning in business intelligence and big data analytics, soft computing, security, cloud computing and the latest trends.
Author: Vanita Jain
Publisher: Springer Nature
ISBN: 9811503729
Category : Technology & Engineering
Languages : en
Pages : 466
Get Book
Book Description
This book gathers the best papers presented at the International Conference on Data Sciences, Security and Applications (ICDSSA 2019), organized by Bharati Vidyapeeth’s College of Engineering, New Delhi, India, on 7–8 March 2019. The respective contributions present original research work, essential information, techniques and applications in the fields of data mining, artificial intelligence and computational intelligence. They also discuss machine learning in business intelligence and big data analytics, soft computing, security, cloud computing and the latest trends.
Author: Marcus A. Maloof
Publisher: Springer Science & Business Media
ISBN: 1846282535
Category : Computers
Languages : en
Pages : 218
Get Book
Book Description
"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information processing and combines and extends results from computer security. The first part of the book surveys the data sources, the learning and mining methods, evaluation methodologies, and past work relevant for computer security. The second part of the book consists of articles written by the top researchers working in this area. These articles deals with topics of host-based intrusion detection through the analysis of audit trails, of command sequences and of system calls as well as network intrusion detection through the analysis of TCP packets and the detection of malicious executables. This book fills the great need for a book that collects and frames work on developing and applying methods from machine learning and data mining to problems in computer security.
Author: Auhood Alfaries
Publisher: Springer Nature
ISBN: 3030363686
Category : Computers
Languages : en
Pages : 353
Get Book
Book Description
This book constitutes the refereed proceedings of the First International Conference on Intelligent Cloud Computing, ICC 2019, held in Riyadh, Saudi Arabia, in December 2019. The two-volume set presents 53 full papers, which were carefully reviewed and selected from 174 submissions. The papers are organized in topical sections on Cyber Security; Data Science; Information Technology and Applications; Network and IoT.
Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 1000557510
Category : Computers
Languages : en
Pages : 430
Get Book
Book Description
Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science. After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media. This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.
Author: Suman Ghosal
Publisher: CRC Press
ISBN: 100056486X
Category : Computers
Languages : en
Pages : 449
Get Book
Book Description
This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective. The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security. Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.
Author: Pallavi Vijay Chavan
Publisher: CRC Press
ISBN: 1000613429
Category : Computers
Languages : en
Pages : 322
Get Book
Book Description
This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance, followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful.
Author: Iván Palomares Carrascosa
Publisher: Springer
ISBN: 3319594397
Category : Computers
Languages : en
Pages : 270
Get Book
Book Description
The book illustrates the inter-relationship between several data management, analytics and decision support techniques and methods commonly adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision support approaches in a myriad of real-life scenarios and problems, with Cybersecurity-related domains being no exception. This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances in Cybersecurity-related applications of data analytics and decision support approaches. In addition to theoretical studies and overviews of existing relevant literature, this book comprises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detection, E-Learning, Online Examinations, Cybersecurity noisy data removal, Secure Smart Power Systems, Security Visualization and Monitoring. Researchers and professionals alike will find the chapters an essential read for further research on the topic.
Author: Auhood Alfaries
Publisher: Springer Nature
ISBN: 3030363651
Category : Computers
Languages : en
Pages : 343
Get Book
Book Description
This book constitutes the refereed proceedings of the First International Conference on Intelligent Cloud Computing, ICC 2019, held in Riyadh, Saudi Arabia, in December 2019. The two-volume set presents 53 full papers, which were carefully reviewed and selected from 174 submissions. The papers are organized in topical sections on Cyber Security; Data Science; Information Technology and Applications; Network and IoT.
Author: Mamoun Alazab
Publisher: Springer
ISBN: 3030130576
Category : Computers
Languages : en
Pages : 246
Get Book
Book Description
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Author: Michael Gertz
Publisher: Springer Science & Business Media
ISBN: 0387485333
Category : Computers
Languages : en
Pages : 577
Get Book
Book Description
Handbook of Database Security: Applications and Trends provides an up-to-date overview of data security models, techniques, and architectures in a variety of data management applications and settings. In addition to providing an overview of data security in different application settings, this book includes an outline for future research directions within the field. The book is designed for industry practitioners and researchers, and is also suitable for advanced-level students in computer science.
