Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices (dhl)

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.

This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.

Key Features:

• This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security.
• It showcases important security aspects and current trends in the field.
• It provides an insight of the future research directions in the field.
• Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.

電腦安全是一個更廣泛的術語，包括技術、協議、標準和政策，以確保計算系統（包括計算機硬件、軟件和其中存儲的信息）的安全性。而網絡安全則是一個特定且不斷發展的領域，旨在保護計算機網絡（離線和在線）免受未經授權的訪問、僵屍網絡、釣魚詐騙等攻擊。機器學習是計算機科學的一個分支，它使計算機能夠根據可觀察和可驗證的數據和信息採用新的行為。它可以應用於通過數據挖掘和其他技術來檢測異常，以確保計算機和信息的安全。

本書將是一個寶貴的資源，用於了解機器學習和數據挖掘在建立計算機和網絡安全方面的重要性。它強調了與計算機和網絡安全相關的重要安全方面，以及基於機器學習和數據挖掘的解決方案的分析。本書還突出了這些解決方案可以應用的未來研究領域。此外，它滿足了IT專業人士、研究人員、教師、科學家、研究生、研究學者和軟件開發人員的需求，他們希望使用基於機器學習的方法在網絡安全領域進行研究和開發對抗性解決方案。對於計算機科學和工程領域以及網絡安全專業人士來說，這是一個豐富的信息來源。

主要特點：
- 本書包含示例和插圖，以演示機器學習和數據挖掘在計算機和網絡安全中的原則、算法、挑戰和應用。
- 它展示了該領域的重要安全方面和當前趨勢。
- 它提供了對該領域未來研究方向的洞察。
- 本書的內容有助於學生更好地理解攻擊者的動機，以及如何使用基於機器學習的方法處理和減輕情況，以更好地進行防禦。

Brij B. Gupta received PhD degree from Indian Institute of Technology Roorkee, India in Information and Cyber Security. He published more than 175 research papers in International Journals and Conferences of high repute including IEEE, Elsevier, ACM, Springer, Wiley, Taylor & Francis, Inderscience, etc. He has visited several countries, i.e. Canada, Japan, Malaysia, Australia, China, Hong-Kong, Italy, Spain etc to present his research work. His biography was selected and published in the 30th Edition of Marquis Who's Who in the World, 2012. Dr. Gupta also received Young Faculty research fellowship award from Ministry of Electronics and Information Technology, Government of India in 2017. He is also working as principal investigator of various R&D projects. He is serving as associate editor of IEEE Access, IEEE TII, and Executive editor of IJITCA, Inderscience, respectively. At present, Dr. Gupta is working as Assistant Professor in the Department of Computer Engineering, National Institute of Technology Kurukshetra India. His research interest includes Information security, Cyber Security, Mobile security, Cloud Computing, Web security, Intrusion detection and Phishing.

Michael Sheng is a full Professor and Head of Department of Computing at Macquarie University. Before moving to Macquarie, Michael spent 10 years at School of Computer Science, the University of Adelaide (UoA). Michael holds a PhD degree in computer science from the University of New South Wales (UNSW) and did his post-doc as a research scientist at CSIRO ICT Centre. From 1999 to 2001, Sheng also worked at UNSW as a visiting research fellow. Prior to that, he spent 6 years as a senior software engineer in industries.

Prof. Sheng has more than 280 publications as edited books and proceedings, refereed book chapters, and refereed technical papers in journals and conferences including ACM Computing Surveys, ACM TOIT, ACM TOMM, ACM TKDD, VLDB Journal, Computer (Oxford), IEEE TPDS, TKDE, DAPD, IEEE TSC, WWWJ, IEEE Computer, IEEE Internet Computing, Communications of the ACM, VLDB, ICDE, ICDM, CIKM, EDBT, WWW, ICSE, ICSOC, ICWS, and CAiSE. Dr. Michael Sheng is the recipient of the ARC Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003). 

Brij B. Gupta在印度羅爾基理工學院獲得資訊與網路安全博士學位。他在國際知名期刊和會議上發表了超過175篇研究論文，包括IEEE、Elsevier、ACM、Springer、Wiley、Taylor & Francis、Inderscience等。他曾訪問過加拿大、日本、馬來西亞、澳大利亞、中國、香港、義大利、西班牙等多個國家，以展示他的研究成果。他的傳記被選為2012年《世界名人錄》第30版中的一部分。2017年，Gupta博士還獲得了印度電子與資訊技術部頒發的青年教師研究獎助金。他還擔任多個研發項目的主要調查員。他分別擔任IEEE Access、IEEE TII的副編輯和IJITCA的執行編輯。目前，Gupta博士在印度國家技術研究所庫魯克薛特拉分校的計算機工程系擔任助理教授。他的研究興趣包括信息安全、網絡安全、移動安全、雲計算、網絡安全、入侵檢測和釣魚。

Michael Sheng是麥覺理大學計算機系的教授和系主任。在加入麥覺理之前，Michael在阿德萊德大學計算機科學學院（UoA）工作了10年。Michael擁有新南威爾士大學（UNSW）的計算機科學博士學位，並在CSIRO ICT Centre擔任研究科學家的博士後研究。從1999年到2001年，Sheng還在UNSW擔任訪問研究員。在此之前，他在工業界擔任高級軟件工程師長達6年。

Sheng教授在編輯的書籍和會議論文、經過審查的專書章節和期刊論文方面發表了超過280篇論文，包括ACM Computing Surveys、ACM TOIT、ACM TOMM、ACM TKDD、VLDB Journal、Computer (Oxford)、IEEE TPDS、TKDE、DAPD、IEEE TSC、WWWJ、IEEE Computer、IEEE Internet Computing、Communications of the ACM、VLDB、ICDE、ICDM、CIKM、EDBT、WWW、ICSE、ICSOC、ICWS和CAiSE等。Michael Sheng博士是ARC Future Fellowship（2014年）、Chris Wallace傑出研究貢獻獎（2012年）和Microsoft Research Fellowship（2003年）的獲獎者。