Deep Learning Approaches to Cloud Security (Hardcover)
暫譯: 雲端安全的深度學習方法 (精裝版)

Rathore, Pramod Singh, Dutt, Vishal, Agrawal, Rashmi

Deep Learning Approaches to Cloud Security (Hardcover)
  • 出版商: Wiley
  • 出版日期: 2022-01-26
  • 售價: $2,080
  • 貴賓價: 9.8 折 $2,038
  • 語言: 英文
  • 頁數: 304
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1119760526
  • ISBN-13: 9781119760528
  • 相關分類: DeepLearning、資訊安全

    • 下單後立即進貨 (約5~7天)

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商品描述

DEEP LEARNING APPROACHES TO CLOUD SECURITY

Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts.

Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field.

This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library.

Deep Learning Approaches to Cloud Security:

  • Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches
  • Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security
  • Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area
  • Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole

Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas

商品描述(中文翻譯)

**深度學習在雲端安全中的應用**

涵蓋當今社會中最重要的主題之一——雲端安全，本編輯團隊深入探討了來自不斷演變的深度學習方法的解決方案，這些解決方案使計算機能夠從經驗中學習，並以概念層次結構的方式理解世界，每個概念通過與更簡單概念的關係來定義。

深度學習是計算機科學中增長最快的領域。深度學習算法和技術在自動機器翻譯、自動手寫生成、視覺識別、詐騙檢測以及檢測兒童發展遲緩等不同領域中被發現是有用的。然而，成功地在這些領域應用深度學習技術或算法需要協同努力，促進來自數據科學到可視化等多個學科專家的綜合研究。本書提供了這些領域中深度學習的最先進方法，包括檢測和預測領域，以及未來框架的開發、服務系統的構建和分析方面。在所有這些主題中，使用了深度學習方法，如人工神經網絡、模糊邏輯、遺傳算法和混合機制。本書旨在處理高效雲端安全系統的建模和性能預測，從而為這一快速發展的領域帶來新的維度。

這本開創性的全新卷冊介紹了深度學習的這些主題和趨勢，彌補了研究空白，並提出了解決工程師或科學家在這一領域每天面臨的挑戰的方案。無論是資深工程師還是學生，這本書都是任何圖書館的必備之選。

**深度學習在雲端安全中的應用：**

- 是首部深入探討通過深度學習方法在雲端安全中最新趨勢和創新的專著
- 涵蓋這些重要的新創新，如人工智慧、數據挖掘及其他與雲端安全相關的計算技術
- 對於在此領域工作的資深計算機科學家或工程師、新進工程師或學生來說，都是一本有用的參考書
- 不僅討論這些技術的實際應用，還探討這些深度學習工具對雲端安全及整個社會的重要性背後的更廣泛概念和理論

**讀者對象：** 計算機科學家、從事資訊技術、設計、網路安全和製造的科學家和工程師、計算機、電子學及電氣和網路安全的研究人員、綜合領域和數據分析的研究人員，以及這些領域的學生

作者簡介

Pramod Singh Rathore, PhD, is an assistant professor in the computer science and engineering department at the Aryabhatta Engineering College and Research Centre, Ajmer, Rajasthan, India and is also visiting faculty at the Government University, MDS Ajmer. He has over eight years of teaching experience and more than 45 publications in peer-reviewed journals, books, and conferences. He has also co-authored and edited numerous books with a variety of global publishers, such as the imprint, Wiley-Scrivener.

Vishal Dutt, PhD, received his doctorate in computer science from the University of Madras, and he is an assistant professor in the computer science and engineering department at the Aryabhatta Engineering College in Ajmer, as well as visiting faculty at Maharshi Dayanand Saraswati University in Ajmer. He has four years of teaching experience and has more than 22 publications in peer-reviewed scientific and technical journals. He has also been working as a freelance writer for more than six years in the fields of data analytics, Java, Assembly Programmer, Desktop Designer, and Android Developer.

Rashmi Agrawal, PhD, is a professor in the Department of Computer Applications at Manav Rachna International Institute of Research and Studies in Faridabad, India. She has over 18 years of experience in teaching and research and is a book series editor for a series on big data and machine learning. She has authored or coauthored numerous research papers in peer-reviewed scientific and technical journals and conferences and has also edited or authored books with a number of large book publishers, in imprints such as Wiley-Scrivener. She is also an active reviewer and editorial board member in various journals.

Satya Murthy Sasubilli is a solutions architect with the Huntington National Bank, having received his masters in computer applications from the University of Madras, India. He has more than 15 years of experience in cloud-based technologies like big data solutions, cloud infrastructure, digital analytics delivery, data warehousing, and many others. He has worked with many Fortune 500 organizations, such as Infosys, Capgemini, and others and is an active reviewer for several scientific and technical journals.

Srinivasa Rao Swarna is a program manager and senior data architect at Tata Consultancy Services in the USA. He received his BTech in chemical engineering from Jawaharlal Nehru Technological University, Hyderabad, India and completed his internship at Volkswagen AG, Wolfsburg, Germany in 2004. He has over 16 years of experience in this area, having worked with many Fortune 500 companies, and he is a frequent reviewer for several scientific and technical journals.

作者簡介(中文翻譯)

Pramod Singh Rathore, PhD, 是印度拉賈斯坦邦阿傑梅爾的阿里亞巴塔工程學院與研究中心計算機科學與工程系的助理教授，同時也是MDS阿傑梅爾政府大學的訪問教員。他擁有超過八年的教學經驗，並在同行評審的期刊、書籍和會議上發表了超過45篇論文。他還與多家全球出版商（如Wiley-Scrivener）共同編著和編輯了多本書籍。

Vishal Dutt, PhD, 於馬德拉斯大學獲得計算機科學博士學位，現為阿里亞巴塔工程學院計算機科學與工程系的助理教授，同時也是阿傑梅爾的馬哈希·達亞南德·薩拉斯瓦蒂大學的訪問教員。他擁有四年的教學經驗，並在同行評審的科學和技術期刊上發表了超過22篇論文。他還在數據分析、Java、組合語言程式設計、桌面設計和Android開發等領域擔任自由作家超過六年。

Rashmi Agrawal, PhD, 是印度法里達巴德Manav Rachna國際研究與學院計算機應用系的教授。她擁有超過18年的教學和研究經驗，並擔任大數據和機器學習系列書籍的系列編輯。她在同行評審的科學和技術期刊及會議上發表了多篇研究論文，並與多家大型出版社（如Wiley-Scrivener）編輯或撰寫了多本書籍。她還是多個期刊的活躍審稿人和編輯委員會成員。

Satya Murthy Sasubilli 是亨廷頓國家銀行的解決方案架構師，擁有印度馬德拉斯大學的計算機應用碩士學位。他在雲端技術方面擁有超過15年的經驗，專注於大數據解決方案、雲基礎設施、數位分析交付、數據倉儲等領域。他曾與多家《財富》500強企業（如Infosys、Capgemini等）合作，並擔任多個科學和技術期刊的活躍審稿人。

Srinivasa Rao Swarna 是美國塔塔顧問服務公司的項目經理和高級數據架構師。他在印度海得拉巴的賈瓦哈拉爾·尼赫魯科技大學獲得化學工程學士學位，並於2004年在德國沃爾夫斯堡的福斯汽車公司完成實習。他在該領域擁有超過16年的經驗，曾與多家《財富》500強公司合作，並經常擔任多個科學和技術期刊的審稿人。

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