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Unsupervised Anomaly Detection Using Bayesian Networks And Gaussian Mixture Models
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Book Synopsis Network Anomaly Detection by : Dhruba Kumar Bhattacharyya
Download or read book Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and published by CRC Press. This book was released on 2013-06-18 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion. In this book, you’ll learn about: Network anomalies and vulnerabilities at various layers The pros and cons of various machine learning techniques and algorithms A taxonomy of attacks based on their characteristics and behavior Feature selection algorithms How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance Important unresolved issues and research challenges that need to be overcome to provide better protection for networks Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.
Book Synopsis Encyclopedia of Biometrics by : Stan Z. Li
Download or read book Encyclopedia of Biometrics written by Stan Z. Li and published by Springer Science & Business Media. This book was released on 2009-08-27 with total page 1466 pages. Available in PDF, EPUB and Kindle. Book excerpt: With an A–Z format, this encyclopedia provides easy access to relevant information on all aspects of biometrics. It features approximately 250 overview entries and 800 definitional entries. Each entry includes a definition, key words, list of synonyms, list of related entries, illustration(s), applications, and a bibliography. Most entries include useful literature references providing the reader with a portal to more detailed information.
Book Synopsis Tenth Scandinavian Conference on Artificial Intelligence by : A. Holst
Download or read book Tenth Scandinavian Conference on Artificial Intelligence written by A. Holst and published by IOS Press. This book was released on 2008-05-19 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Scandinavian Conference on Artificial Intelligence continues a tradition of being one of the most important regional AI conferences in Europe for ten years now. The topics of this year’s contributions have a broad range, from machine learning, knowledge representation, robotics, planning and scheduling, natural language, computer vision, search algorithms, industrial applications, to philosophical foundations. These contributions exemplify the diversity of research in artificial intelligence today and confirm the achievement and magnitude of 25 years AI research in Scandinavia. In this tenth edition there will be an overview of the past, present and future of artificial intelligence. Furthermore, attention will be paid to the industrial aspects of artificial intelligence and the impressions from Swedish AI through the years. Other topics discussed are biosurveillance and an elaboration on probalistic modelling and learning in a relational world.
Book Synopsis Network and System Security by : Mirosław Kutyłowski
Download or read book Network and System Security written by Mirosław Kutyłowski and published by Springer Nature. This book was released on 2020-12-18 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Network and System Security, NSS 2020, held in Melbourne, VIC, Australia, in November 2020. The 17 full and 9 short papers were carefully reviewed and selected from 60 submissions. The selected papers are devoted to topics such as secure operating system architectures, applications programming and security testing, intrusion and attack detection, cybersecurity intelligence, access control, cryptographic techniques, cryptocurrencies, ransomware, anonymity, trust, recommendation systems, as well machine learning problems. Due to the Corona pandemic the event was held virtually.
Book Synopsis Artificial Intelligence Applications and Innovations by : Ilias Maglogiannis
Download or read book Artificial Intelligence Applications and Innovations written by Ilias Maglogiannis and published by Springer Nature. This book was released on with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning for Cyber Security by : Yuan Xu
Download or read book Machine Learning for Cyber Security written by Yuan Xu and published by Springer Nature. This book was released on 2023-01-12 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.
Book Synopsis Mixture Models and Applications by : Nizar Bouguila
Download or read book Mixture Models and Applications written by Nizar Bouguila and published by Springer. This book was released on 2019-08-13 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent advances, approaches, theories and applications related to mixture models. In particular, it presents recent unsupervised and semi-supervised frameworks that consider mixture models as their main tool. The chapters considers mixture models involving several interesting and challenging problems such as parameters estimation, model selection, feature selection, etc. The goal of this book is to summarize the recent advances and modern approaches related to these problems. Each contributor presents novel research, a practical study, or novel applications based on mixture models, or a survey of the literature. Reports advances on classic problems in mixture modeling such as parameter estimation, model selection, and feature selection; Present theoretical and practical developments in mixture-based modeling and their importance in different applications; Discusses perspectives and challenging future works related to mixture modeling.
Book Synopsis Data Literacy with Python by : Oswald Campesato
Download or read book Data Literacy with Python written by Oswald Campesato and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-11-20 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to usher readers into the world of data, ensuring a comprehensive understanding of its nuances, intricacies, and complexities. With Python 3 as the primary medium, the book underscores the pivotal role of data in modernindustries, and how its adept management can lead to insightful decision-making. The book provides a quick introduction to foundational data-related tasks, priming the readers for more advanced concepts of model training introduced later on. Through detailed, step-by-step Python code examples, the reader will master training models, beginning with the kNN algorithm, and then smoothly transitioning to other classifiers, by tweaking mere lines of code. Tools like Sweetviz, Skimpy, Matplotlib, and Seaborn are introduced, offering readers a hands-on experience in rendering charts and graphs. Companion files with source code and data sets are available by writing to the publisher. FEATURES: Introduces tools like Sweetviz, Skimpy, Matplotlib, and Seaborn offering readers a hands-on experience in rendering charts and graphs Companion files with numerous Python code samples
Book Synopsis Progress in Systems Engineering by : Henry Selvaraj
Download or read book Progress in Systems Engineering written by Henry Selvaraj and published by Springer. This book was released on 2014-08-12 with total page 846 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of proceedings from the International Conference on Systems Engineering, Las Vegas, 2014 is orientated toward systems engineering, including topics like aero-space, power systems, industrial automation and robotics, systems theory, control theory, artificial intelligence, signal processing, decision support, pattern recognition and machine learning, information and communication technologies, image processing, and computer vision as well as its applications. The volume’s main focus is on models, algorithms, and software tools that facilitate efficient and convenient utilization of modern achievements in systems engineering.
Book Synopsis Network Optimization in Intelligent Internet of Things Applications by : Payal Khurana Batra
Download or read book Network Optimization in Intelligent Internet of Things Applications written by Payal Khurana Batra and published by CRC Press. This book was released on 2024-09-25 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network Optimization in Intelligent Internet of Things Applications: Principles and Challenges sheds light on the optimization methods that form the basis of effective communication between networked devices. It is an excellent resource as it provides readers with a thorough understanding of the methods, ideas, and tactics essential to attaining seamless connectivity and improving performance. This book presents the fundamental ideas that govern network optimization, from maximizing throughput and lowering latency to handling a variety of communication protocols and minimizing energy use. It also addresses scalability issues, security flaws, and constantly changing IoT environments along with optimization techniques. This book uses cutting-edge research and real-world examples to give readers the knowledge and skills to address the complex problems associated with network optimization in intelligent IoT applications. It also examines machine learning-driven predictive analytics, robust security protocols, flexible routing algorithms, and the integration of edge computing - all crucial instruments for overcoming obstacles and attaining peak performance. This book provides a comprehensive understanding of the principles, challenges, and cutting-edge solutions in IoT network optimization for all kinds of readers, whether it is students, academicians, researchers, or industry professionals. This book unleashes the potential of networked smart devices, which can be unleashed in various sectors.
Book Synopsis Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by : Aurélien Géron
Download or read book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow written by Aurélien Géron and published by "O'Reilly Media, Inc.". This book was released on 2019-09-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
Book Synopsis Hands-On Unsupervised Learning with Python by : Giuseppe Bonaccorso
Download or read book Hands-On Unsupervised Learning with Python written by Giuseppe Bonaccorso and published by Packt Publishing Ltd. This book was released on 2019-02-28 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the skill-sets required to implement various approaches to Machine Learning with Python Key FeaturesExplore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and moreBuild your own neural network models using modern Python librariesPractical examples show you how to implement different machine learning and deep learning techniquesBook Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learnUse cluster algorithms to identify and optimize natural groups of dataExplore advanced non-linear and hierarchical clustering in actionSoft label assignments for fuzzy c-means and Gaussian mixture modelsDetect anomalies through density estimationPerform principal component analysis using neural network modelsCreate unsupervised models using GANsWho this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.
Book Synopsis Automated Data Analytics by : Soraya Sedkaoui
Download or read book Automated Data Analytics written by Soraya Sedkaoui and published by John Wiley & Sons. This book was released on 2024-10-11 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: The human mind is endowed with a remarkable capacity for creative synthesis between intuition and reason; this mental alchemy is the source of genius. A new synergy is emerging between human ingenuity and the computational capacity of generative AI models. Automated Data Analytics focuses on this fruitful collaboration between the two to unlock the full potential of data analysis. Together, human ethics and algorithmic productivity have created an alloy stronger than the sum of its parts. The future belongs to this symbiosis between heart and mind, human and machine. If we succeed in harmoniously combining our strengths, it will only be a matter of time before we discover new analytical horizons. This book sets out the foundations of this promising partnership, in which everyone makes their contribution to a common work of considerable scope. History is being forged before our very eyes. It is our responsibility to write it wisely, and to collectively pursue the ideal of augmented intelligence progress.
Book Synopsis Computer Security. ESORICS 2023 International Workshops by : Sokratis Katsikas
Download or read book Computer Security. ESORICS 2023 International Workshops written by Sokratis Katsikas and published by Springer Nature. This book was released on with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Analytics and Machine Learning by : Pushpa Singh
Download or read book Data Analytics and Machine Learning written by Pushpa Singh and published by Springer Nature. This book was released on with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning and Knowledge Discovery in Databases. Research Track by : Nuria Oliver
Download or read book Machine Learning and Knowledge Discovery in Databases. Research Track written by Nuria Oliver and published by Springer Nature. This book was released on 2021-09-09 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.
Book Synopsis Deep Generative Models by : Anirban Mukhopadhyay
Download or read book Deep Generative Models written by Anirban Mukhopadhyay and published by Springer Nature. This book was released on 2022-10-07 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second MICCAI Workshop on Deep Generative Models, DG4MICCAI 2022, held in conjunction with MICCAI 2022, in September 2022. The workshops took place in Singapore. DG4MICCAI 2022 accepted 12 papers from the 15 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community.
