Advanced Techniques For Anomaly Detection
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Advanced Techniques For Anomaly Detection
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Author : Abdul Wahid
language : en
Publisher: CRC Press
Release Date : 2025-04-03
Advanced Techniques For Anomaly Detection written by Abdul Wahid and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-03 with Computers categories.
The book will also summarize various protocols that work based on learning strategies and applied intelligence in the context of IoT environments.
Anomaly Detection
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Author : Saira Banu
language : en
Publisher: Nova Science Publishers
Release Date : 2021
Anomaly Detection written by Saira Banu and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Anomaly detection (Computer security) categories.
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data. This book will mainly target researchers and higher graduate learners in computer science and data science.
Innovations And Advanced Techniques In Computer And Information Sciences And Engineering
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Author : Tarek Sobh
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-04
Innovations And Advanced Techniques In Computer And Information Sciences And Engineering written by Tarek Sobh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-04 with Technology & Engineering categories.
This book includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Computer Engineering and Information Sciences. The book presents selected papers from the conference proceedings of the International Conference on Systems, Computing Sciences and Software Engineering (SCSS 2006). All aspects of the conference were managed on-line.
Anomaly Detection For Innovators Transforming Data Into Breakthroughs
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Author : Vinayak Pillai
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2022-04-22
Anomaly Detection For Innovators Transforming Data Into Breakthroughs written by Vinayak Pillai and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-22 with Computers categories.
"Anomaly Detection for Innovators: Transforming Data into Breakthroughs" is a guide for professionals and data enthusiasts looking to harness the power of anomaly detection to revolutionize their data-driven decision-making processes. By blending foundational principles with cutting-edge technologies, the book explores how to design, optimize, and implement anomaly detection systems across industries, particularly in financial and insurance sectors. Each chapter delves into a unique aspect of anomaly detection, from building robust data systems to implementing predictive analytics, while offering actionable insights for creating efficient and scalable data models. This book empowers readers to translate data anomalies into opportunities for groundbreaking innovation.
Outlier Analysis
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2016-12-10
Outlier Analysis written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-10 with Computers categories.
This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods. Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data. Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner. The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.
Control Charts And Machine Learning For Anomaly Detection In Manufacturing
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Author : Kim Phuc Tran
language : en
Publisher: Springer Nature
Release Date : 2021-08-29
Control Charts And Machine Learning For Anomaly Detection In Manufacturing written by Kim Phuc Tran and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-29 with Technology & Engineering categories.
This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.
Outlier Ensembles
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2017-04-06
Outlier Ensembles written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-06 with Computers categories.
This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. In addition, it covers the techniques with which such methods can be made more effective. A formal classification of these methods is provided, and the circumstances in which they work well are examined. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification. The similarities and (subtle) differences in the ensemble techniques for the classification and outlier detection problems are explored. These subtle differences do impact the design of ensemble algorithms for the latter problem. This book can be used for courses in data mining and related curricula. Many illustrative examples and exercises are provided in order to facilitate classroom teaching. A familiarity is assumed to the outlier detection problem and also to generic problem of ensemble analysis in classification. This is because many of the ensemble methods discussed in this book are adaptations from their counterparts in the classification domain. Some techniques explained in this book, such as wagging, randomized feature weighting, and geometric subsampling, provide new insights that are not available elsewhere. Also included is an analysis of the performance of various types of base detectors and their relative effectiveness. The book is valuable for researchers and practitioners for leveraging ensemble methods into optimal algorithmic design.
Advanced Research Trends In Sustainable Solutions Data Analytics And Security
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Author : Radwan, Ahmed Gomaa
language : en
Publisher: IGI Global
Release Date : 2025-01-03
Advanced Research Trends In Sustainable Solutions Data Analytics And Security written by Radwan, Ahmed Gomaa and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Business & Economics categories.
In the rapidly evolving landscape of technology, innovation, and sustainability, there is a growing need to explore advanced research trends that shape our understanding and implementation of solutions for a sustainable future. Emerging fields such as renewable energy, artificial intelligence (AI), and circular economy principles are at the forefront of this exploration, driving transformative changes across industries. Understanding these trends allows us to create resilient solutions to promote economic growth, environmental protection, and social well-being. This commitment to innovation and sustainability will be essential for fostering a balanced and prosperous future. Advanced Research Trends in Sustainable Solutions, Data Analytics, and Security introduces new research trends that could change how we perceive, use, and integrate technology in a rapidly changing world. It advances the understanding of how technology and innovation can contribute to sustainable development, fostering interdisciplinary collaborations that transcend traditional boundaries, and inspiring actionable initiatives that address global challenges. Covering topics such as artificial intelligence (AI), green infrastructure, and sustainable tourism, this book is an excellent resource for researchers, practitioners, policymakers, academicians, and more.
Handbook Of Ai Driven Threat Detection And Prevention
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Author : Pankaj Bhambri
language : en
Publisher: CRC Press
Release Date : 2025-06-12
Handbook Of Ai Driven Threat Detection And Prevention written by Pankaj Bhambri and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-12 with Technology & Engineering categories.
In today’s digital age, the risks to data and infrastructure have increased in both range and complexity. As a result, companies need to adopt cutting-edge artificial intelligence (AI) solutions to effectively detect and counter potential threats. This handbook fills the existing knowledge gap by bringing together a team of experts to discuss the latest advancements in security systems powered by AI. The handbook offers valuable insights on proactive strategies, threat mitigation techniques, and comprehensive tactics for safeguarding sensitive data. Handbook of AI-Driven Threat Detection and Prevention: A Holistic Approach to Security explores AI-driven threat detection and prevention, and covers a wide array of topics such as machine learning algorithms, deep learning, natural language processing, and so on. The holistic view offers a deep understanding of the subject matter as it brings together insights and contributions from experts from around the world and various disciplines including computer science, cybersecurity, data science, and ethics. This comprehensive resource provides a well-rounded perspective on the topic and includes real-world applications of AI in threat detection and prevention emphasized through case studies and practical examples that showcase how AI technologies are currently being utilized to enhance security measures. Ethical considerations in AI-driven security are highlighted, addressing important questions related to privacy, bias, and the responsible use of AI in a security context. The investigation of emerging trends and future possibilities in AI-driven security offers insights into the potential impact of technologies like quantum computing and blockchain on threat detection and prevention. This handbook serves as a valuable resource for security professionals, researchers, policymakers, and individuals interested in understanding the intersection of AI and security. It equips readers with the knowledge and expertise to navigate the complex world of AI-driven threat detection and prevention. This is accomplished by synthesizing current research, insights, and real-world experiences.
Reshaping Cybersecurity With Generative Ai Techniques
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Author : Jhanjhi, Noor Zaman
language : en
Publisher: IGI Global
Release Date : 2024-09-13
Reshaping Cybersecurity With Generative Ai Techniques written by Jhanjhi, Noor Zaman and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-13 with Computers categories.
The constantly changing digital environment of today makes cybersecurity an ever-increasing concern. With every technological advancement, cyber threats become more sophisticated and easily exploit system vulnerabilities. This unending attack barrage exposes organizations to data breaches, financial losses, and reputational harm. The traditional defense mechanisms, once dependable, now require additional support to keep up with the dynamic nature of modern attacks. Reshaping CyberSecurity With Generative AI Techniques offers a transformative solution to the pressing cybersecurity dilemma by harnessing the power of cutting-edge generative AI technologies. Bridging the gap between artificial intelligence and cybersecurity presents a paradigm shift in defense strategies, empowering organizations to safeguard their digital assets proactively. Through a comprehensive exploration of generative AI techniques, readers gain invaluable insights into how these technologies can be leveraged to mitigate cyber threats, enhance defense capabilities, and reshape the cybersecurity paradigm.