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Machine Learning Techniques And Analytics For Cloud Security


Machine Learning Techniques And Analytics For Cloud Security
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Machine Learning Techniques And Analytics For Cloud Security


Machine Learning Techniques And Analytics For Cloud Security
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Author : Rajdeep Chakraborty
language : en
Publisher: John Wiley & Sons
Release Date : 2021-11-30

Machine Learning Techniques And Analytics For Cloud Security written by Rajdeep Chakraborty and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-30 with Computers categories.


MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.



Introduction To Machine Learning In The Cloud With Python


Introduction To Machine Learning In The Cloud With Python
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Author : Pramod Gupta
language : en
Publisher: Springer Nature
Release Date : 2021-04-28

Introduction To Machine Learning In The Cloud With Python written by Pramod Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Technology & Engineering categories.


This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.



Cyber Security And Digital Forensics


Cyber Security And Digital Forensics
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Author : Mangesh M. Ghonge
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-12

Cyber Security And Digital Forensics written by Mangesh M. Ghonge and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-12 with Computers categories.


CYBER SECURITY AND DIGITAL FORENSICS Cyber security is an incredibly important issue that is constantly changing, with new methods, processes, and technologies coming online all the time. Books like this are invaluable to professionals working in this area, to stay abreast of all of these changes. Current cyber threats are getting more complicated and advanced with the rapid evolution of adversarial techniques. Networked computing and portable electronic devices have broadened the role of digital forensics beyond traditional investigations into computer crime. The overall increase in the use of computers as a way of storing and retrieving high-security information requires appropriate security measures to protect the entire computing and communication scenario worldwide. Further, with the introduction of the internet and its underlying technology, facets of information security are becoming a primary concern to protect networks and cyber infrastructures from various threats. This groundbreaking new volume, written and edited by a wide range of professionals in this area, covers broad technical and socio-economic perspectives for the utilization of information and communication technologies and the development of practical solutions in cyber security and digital forensics. Not just for the professional working in the field, but also for the student or academic on the university level, this is a must-have for any library. Audience: Practitioners, consultants, engineers, academics, and other professionals working in the areas of cyber analysis, cyber security, homeland security, national defense, the protection of national critical infrastructures, cyber-crime, cyber vulnerabilities, cyber-attacks related to network systems, cyber threat reduction planning, and those who provide leadership in cyber security management both in public and private sectors



Machine Learning And Security


Machine Learning And Security
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Author : Clarence Chio
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-01-26

Machine Learning And Security written by Clarence Chio and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-26 with Computers categories.


Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions



Artificial Intelligence For Cloud And Edge Computing


Artificial Intelligence For Cloud And Edge Computing
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Author : Sanjay Misra
language : en
Publisher: Springer
Release Date : 2023-01-15

Artificial Intelligence For Cloud And Edge Computing written by Sanjay Misra and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-15 with Computers categories.


This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.



Cloud Computing For Machine Learning And Cognitive Applications


Cloud Computing For Machine Learning And Cognitive Applications
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Author : Kai Hwang
language : en
Publisher: MIT Press
Release Date : 2017-06-16

Cloud Computing For Machine Learning And Cognitive Applications written by Kai Hwang and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-16 with Computers categories.


The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data. This textbook is designed to train college students to master modern cloud computing systems in operating principles, architecture design, machine learning algorithms, programming models and software tools for big data mining, analytics, and cognitive applications. The book will be suitable for use in one-semester computer science or electrical engineering courses on cloud computing, machine learning, cloud programming, cognitive computing, or big data science. The book will also be very useful as a reference for professionals who want to work in cloud computing and data science. Cloud and Cognitive Computing begins with two introductory chapters on fundamentals of cloud computing, data science, and adaptive computing that lay the foundation for the rest of the book. Subsequent chapters cover topics including cloud architecture, mashup services, virtual machines, Docker containers, mobile clouds, IoT and AI, inter-cloud mashups, and cloud performance and benchmarks, with a focus on Google's Brain Project, DeepMind, and X-Lab programs, IBKai HwangM SyNapse, Bluemix programs, cognitive initiatives, and neurocomputers. The book then covers machine learning algorithms and cloud programming software tools and application development, applying the tools in machine learning, social media, deep learning, and cognitive applications. All cloud systems are illustrated with big data and cognitive application examples.



Handbook Of Research On Machine And Deep Learning Applications For Cyber Security


Handbook Of Research On Machine And Deep Learning Applications For Cyber Security
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Author : Padmavathi Ganapathi
language : en
Publisher: IGI Global, Information Science Reference
Release Date : 2019-07-26

Handbook Of Research On Machine And Deep Learning Applications For Cyber Security written by Padmavathi Ganapathi and has been published by IGI Global, Information Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Computers categories.


"This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"--



Machine Learning And Data Science


Machine Learning And Data Science
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Author : Prateek Agrawal
language : en
Publisher: John Wiley & Sons
Release Date : 2022-08-09

Machine Learning And Data Science written by Prateek Agrawal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-09 with Computers categories.


MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms. These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.



Hands On Machine Learning For Cybersecurity


Hands On Machine Learning For Cybersecurity
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Author : Soma Halder
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31

Hands On Machine Learning For Cybersecurity written by Soma Halder and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.


Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book



Explainable Machine Learning Models And Architectures


Explainable Machine Learning Models And Architectures
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Author : Suman Lata Tripathi
language : en
Publisher: John Wiley & Sons
Release Date : 2023-09-26

Explainable Machine Learning Models And Architectures written by Suman Lata Tripathi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-26 with Computers categories.


EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.