Ai, Machine Learning and Deep Learning: A Security Perspective

Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use.

While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security).

Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects:

1. This is the first book to explain various practical attacks and countermeasures to AI systems.
2. Both quantitative math models and practical security implementations are provided.
3. It covers both "securing the AI system itself" and "using AI to achieve security".
4. It covers all the advanced AI attacks and threats with detailed attack models.
5. It provides multiple solution spaces to the security and privacy issues in AI tools.
6. The differences among ML and DL security and privacy issues are explained.
7. Many practical security applications are covered.

如今，人工智慧（AI）和機器學習/深度學習（ML/DL）已成為資訊科技中最熱門的領域。在我們的社會中，許多智能設備依賴AI/ML/DL算法/工具進行智能操作。儘管AI/ML/DL算法和工具已被應用於許多互聯網應用和電子設備中，但它們也容易受到各種攻擊和威脅。內部攻擊者可能扭曲AI參數；對手可能污染DL輸入樣本；ML模型可能被改變的分類邊界誤導，還有許多其他攻擊和威脅。這些攻擊可能使AI產品變得危險。

雖然本文討論的重點是AI/ML/DL系統的安全問題（即保護智能系統本身），但AI/ML/DL模型和算法實際上也可以用於網絡安全（即使用AI實現安全性）。

由於AI/ML/DL安全是一個新興領域，許多研究人員和行業專業人士尚未完全了解這個領域。本書旨在提供對各種應用中相關安全問題的挑戰和解決方案的完整概述。它解釋了在先進的AI工具中可能發生的不同攻擊方式以及克服這些攻擊的挑戰。然後，本書描述了許多有前景的解決方案集，以實現AI安全和隱私。本書的特點有以下七個方面：

1. 這是第一本解釋各種實際攻擊和對抗AI系統的書籍。
2. 提供了定量數學模型和實際安全實施。
3. 同時涵蓋了“保護AI系統本身”和“使用AI實現安全”。
4. 詳細介紹了所有先進的AI攻擊和威脅。
5. 提供了多個解決方案空間以解決AI工具中的安全和隱私問題。
6. 解釋了ML和DL安全和隱私問題之間的差異。
7. 涵蓋了許多實際的安全應用。

Dr. Fei Hu is a professor in the department of Electrical and Computer Engineering at the University of Alabama. He has published over 10 technical books with CRC press. His research focus includes cyber security and networking. He obtained his Ph.D. degrees at Tongji University (Shanghai, China) in the field of Signal Processing (in 1999), and at Clarkson University (New York, USA) in Electrical and Computer Engineering (in 2002). He has published over 200 journal/conference papers and books. Dr. Hu's research has been supported by U.S. National Science Foundation, Cisco, Sprint, and other sources. He won the school's President's Faculty Research Award (

Dr. Xiali (Sharon) Hei is an assistant professor in the School of Computing and Informatics at the University of Louisiana at Lafayette. Her research focus is cyber and physical security. Prior to joining the University of Louisiana at Lafayette, she was an assistant professor at Delaware State University from 2015-2017 and Frostburg State University 2014-2015. Sharon received his Ph.D. in computer science from Temple University in 2014, focusing on computer security.

Dr. Fei Hu是阿拉巴馬大學電機與計算機工程系的教授。他與CRC出版社合作出版了超過10本技術書籍。他的研究重點包括網絡安全和網絡技術。他在1999年獲得同濟大學（中國上海）的信號處理博士學位，並在2002年獲得克拉克森大學（美國紐約）的電機與計算機工程博士學位。他已發表了200多篇期刊/會議論文和書籍。Hu博士的研究得到了美國國家科學基金會、思科、Sprint和其他資助機構的支持。他曾獲得該校校長教師研究獎。

Dr. Xiali (Sharon) Hei是路易斯安那大學拉斐特分校計算機與信息學院的助理教授。她的研究重點是網絡和物理安全。在加入路易斯安那大學拉斐特分校之前，她曾在2015年至2017年間擔任特拉華州立大學的助理教授，並在2014年至2015年間擔任弗羅斯特堡州立大學的助理教授。Sharon於2014年從天普大學獲得計算機科學博士學位，專攻計算機安全。