商品描述
This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity.
This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It's not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more.
Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.
商品描述(中文翻譯)
本書探討了機器學習、深度學習和人工智慧在網絡安全領域中的新應用和創新。提供的研究不僅僅是將人工智慧技術應用於數據集，而是深入探討深度學習和網絡安全之間的更深層次問題。
本書還提供了對安全領域中人工智慧中困難的「如何」和「為什麼」問題的洞察。例如，本書包括了關於「可解釋的人工智慧」、「對抗性學習」、「強韌的人工智慧」以及各種相關主題的章節。它不僅限於特定的網絡安全子主題，章節觸及了從惡意軟件到生物識別等各種網絡安全領域。
研究人員和高級學生在網絡安全（同等於信息安全）或人工智慧（包括深度學習、機器學習、大數據和相關領域）領域工作和學習的人會希望購買本書作為參考。在這些領域工作的從業人員也會對購買本書感興趣。
作者簡介
Mark Stamp has extensive experience in information security and machine learning, having worked in these fields within academic, industrial, and government environments. After completing his PhD research in cryptography at Texas Tech University, he spent more than seven years as a cryptanalyst with the United States National Security Agency (NSA), followed by two years developing a security product for a Silicon Valley start-up company. Since early in the present century, Dr. Stamp has been employed as a Professor in the Department of Computer Science at San Jose State University, where he teaches courses in machine learning and information security. To date, he has published more than 150 research articles, most of which deal with problems at the interface between machine learning and information security. Dr. Stamp served as a co-editor of the Handbook of Information and Communication Security (Springer, 2010) and Malware Analysis using Artificial Intelligence and Deep Learning (Springer 2020), and he is the author of multiple textbooks, including Information Security: Principles and Practice (Wiley, 3rd edition, 2021) and Introduction to Machine Learning with Applications in Information Security (Chapman and Hall/CRC, 2nd edition, 2022).
Corrado Aaron Visaggio is an associate professor at the Department of Engineering of the University of Sannio, where he teaches "Security of Networks and Software Systems" at the MSc in Computer Engineering. Currently he is also Chief Scientist Officer at Defence Tech, a company operating in Cybersecurity, Aerospace and Military Engineering. He obtained the MSc in Electronic Engineering (2001) from Politecnico di Bari, and the PhD in Information Engineering (2005) from University of Sannio. His main research interests are: malware analysis, data protection, data protection, threat intelligence. He teaches in Master Programs of Cybersecurity of University of Rome "Tor Vergata", and the International School against organized crime organized by the Italian Ministry of Interior for the education of International Law Enforcement Agencies, and has been instructor at the Department of Intelligence, at the Italian Ministry of Interior. He is director of the Unisannio Chapter of the CINI Cybersecurity National Lab. He is in the Organizing Board of CINI Cybersecurity National Lab. He leads the Cybersecurity Lab at the Department of Engineering of University of Sannio. He is the scientific leader of several research projects in Cybersecurity, funded by Private and Public Organizations. He collaborates with several Universities (ETH Zurich, University of San Jose, University of Castilla-La-Mancha, University of Lugano, University College Dublin, University of Delft, Cochin University of Science & Technology and SCMS School of Engineering & Technology). He has authored more than one hundred scientific papers and he serves in the Editorial Boards of International journals and Program Committees of international Conferences. He is among the founders of the SER&Practice software house, and SLIMER software House.
Fabio Di Troia is an Assistant Professor in the Computer Science department at San Jose State University, where he teaches information security and machine learning courses. He completed his PhD in computer science at Kingston University, London, researching applications of machine learning in the field of cybersecurity. His areas of focus are malware detection, malware design, cryptology, biometrics, and access control. In collaboration with colleagues sharing similar academic background, he co-founded the Silicon Valley Cybersecurity Institute (SVCSI) in 2019, a non-profit organization that aims to increase awareness in the cybersecurity domain for high-school, undergraduate, and graduate students, with particular emphasis in the underrepresented community. Within this organization, he holds the role of program director in software security, and he is also the program committee chair for the Silicon Valley Cybersecurity Conference (SVCC).
Francesco Mercaldo received his master degree in computer engineering from the University of Sannio (Benevento, Italy), with a thesis in software testing. He obtained his Ph.D. in 2015 with a dissertation on malware analysis using machine learning techniques. The research areas of Francesco are software testing, verification, and validation, with the emphasis on the application of empirical methods. Currently, he is working as Researcher at the University of Molise (Italy). He has written almost seventy papers for international journals and conferences.
作者簡介(中文翻譯)
Mark Stamp在信息安全和機器學習領域擁有豐富的經驗，在學術、工業和政府環境中工作過。在德克薩斯理工大學完成他的密碼學博士研究後，他在美國國家安全局（NSA）擔任密碼分析師超過七年，之後又在矽谷一家初創公司開發安全產品工作了兩年。自本世紀初以來，Stamp博士一直在聖荷西州立大學計算機科學系擔任教授，教授機器學習和信息安全課程。迄今為止，他已發表了150多篇研究論文，其中大部分涉及機器學習和信息安全之間的問題。Stamp博士擔任《信息和通信安全手冊》（Springer，2010年）和《使用人工智能和深度學習進行惡意軟件分析》（Springer，2020年）的合編者，並且是多本教科書的作者，包括《信息安全：原理與實踐》（Wiley，第3版，2021年）和《機器學習入門及其在信息安全中的應用》（Chapman and Hall/CRC，第2版，2022年）。
Corrado Aaron Visaggio是Sannio大學工程系的副教授，他在計算機工程碩士課程中教授“網絡和軟件系統安全”。目前，他還是Defence Tech的首席科學家，該公司從事網絡安全、航空航天和軍事工程。他在Bari理工大學獲得電子工程碩士學位（2001年），並在Sannio大學獲得信息工程博士學位（2005年）。他的主要研究興趣包括惡意軟件分析、數據保護、威脅情報。他在羅馬“托爾韋加塔大學”的網絡安全碩士課程和意大利內政部組織的國際打擊有組織犯罪教育的國際執法機構教授課程，並曾在意大利內政部情報部門擔任講師。他是CINI網絡安全國家實驗室Sannio分部的主任，也是CINI網絡安全國家實驗室的組織委員會成員。他領導Sannio大學工程系的網絡安全實驗室。他是由私營和公共組織資助的多個網絡安全研究項目的科學負責人。他與多所大學合作（ETH Zurich，San Jose大學，Castilla-La-Mancha大學，Lugano大學，University College Dublin，Delft大學，Cochin科技大學和SCMS工程技術學院）。他撰寫了100多篇科學論文，並在國際期刊的編輯委員會和國際會議的程序委員會中擔任職務。他是SER＆Practice軟件公司和SLIMER軟件公司的創始人之一。
Fabio Di Troia是聖荷西州立大學計算機科學系的助理教授，教授信息安全和機器學習課程。他在倫敦金斯頓大學完成了計算機科學博士學位，研究機器學習在網絡安全領域的應用。他的研究重點是惡意軟件檢測、惡意軟件設計、密碼學、生物識別和訪問控制。他與具有相似學術背景的同事合作，於2019年共同創辦了矽谷網絡安全學院（SVCSI），這是一家非營利組織，旨在提高高中、本科和研究生學生對網絡安全領域的認識，特別強調在弱勢社區中的推廣。在這個組織中，他擔任軟件安全項目主任的職務，同時他也是
