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This book will help you comprehend the impact of artificial intelligence (AI) on information security, data privacy, and data security. The book starts by explaining the basics and setting the goals for a complete understanding of how AI, Information Security, Data Privacy, and Data Security all connect. Then, it gives you important information about the basics of AI, machine learning, and deep learning in simple terms. It also talks about the ethics of using AI in privacy and security, making sure you understand the power and responsibility that come with AI. Next, it takes you through the…mehr
This book will help you comprehend the impact of artificial intelligence (AI) on information security, data privacy, and data security.
The book starts by explaining the basics and setting the goals for a complete understanding of how AI, Information Security, Data Privacy, and Data Security all connect. Then, it gives you important information about the basics of AI, machine learning, and deep learning in simple terms. It also talks about the ethics of using AI in privacy and security, making sure you understand the power and responsibility that come with AI. Next, it takes you through the complex world of information security and data privacy. It covers everything from the current state of security to how AI can detect threats and protect privacy. Additionally, it delves into ethical considerations to ensure the responsible use of AI in managing data privacy. Later chapters discuss strategies and future trends in using AI for data security, finding the right balance between security and privacy, and giving useful advice for organizations.
In the end, this book examines the current landscape and foresees the future, underscoring the vital importance of maintaining a balance between innovation and privacy in AI-powered security.
What you will learn:
How AI is being used to detect and prevent cyberattacks in real-time
What are the AI-powered techniques for anonymizing and de-identifying data,
What are the latest advancements in AI-powered privacy-enhancing technologies (PETs)
How to find the right balance between security and privacy
Who this book is for:
Information security professionals, data scientists, and software developers seeking to gain an understanding of the latest trends and techniques in AI for information security
Ranadeep Reddy Palle has over 12 years of experience and specializes in the development of distributed and scalable Microservices. His proficiency extends to deploying these Microservices on major cloud platforms like AWS and Azure, always prioritizing strict adherence to privacy and cybersecurity standards. Ranadeep has contributed extensively to journals, particularly in critical domains such as machine learning, AI, Cloud Computing, and data analytics. Holding diverse certifications in both Amazon Web Services (AWS) and Microsoft Azure, he currently serves as a Senior Software Engineer at Zoom in Austin, TX. In this role, he leads a team in implementing cutting-edge solutions and plays a crucial part in the design and development of Microservices for Consent Management, ensuring compliance with global privacy regulations. Ranadeep holds a Master's degree in Computer Science from the University of Houston, Texas.
Krishna Chaitanya Rao Kathala is a prominent researcher in the field of Data Science, Analytics, Machine Learning, and AI, a Ph.D Candidate at the University of Massachusetts Amherst. With over 8 years of specialized experience in AI, Krishna's expertise covers a wide range of topics within Artificial Intelligence, including Generative AI, Ethics, Bias, Fairness, and Safe/Secure AI. He is a prolific scholar, having co-authored 2 books and secured more than 5 international patents. Additionally, Krishna has authored over 8 research papers published in prestigious journals. His influence in the academic and professional realms is widespread, often serving as a judge at more than 10 national and international events, including research symposiums and hackathons. Krishna also contributes actively to the academic community through roles on editorial boards, reviews, and program committees at various conferences. Krishna's merit in the field has led to invitations to speak at distinguished international forums such as the United Nations, the Ministry of Foreign Affairs Ukraine, UNESCO, UNDP, United Nations Women, the Office of the United Nations High Commissioner for Human Rights, and the Talent AI Foundation. His research excellence has been recognized with numerous significant awards and scholarships, highlighting his impactful contributions to AI and technology. He currently holds a leadership position as a Co-Chair at the Northeastern Educational Research Association, Inc., based in Boston, Massachusetts.
Krishna is also an active member of the International Society for Technology in Education (ISTE) and the International Association of Engineers - Hong Kong. Beyond his research and professional activities, Krishna is deeply committed to mentoring, particularly focused on supporting first-generation, under-represented, and marginalized students in STEM fields. His dedication to fostering inclusivity and diversity within the tech community underscores his commitment to using his expertise to make a positive societal impact. Krishna holds a Masters degree in Data Science from University of Massachusetts Amherst.
Inhaltsangabe
1. INTRODUCTION.- 2. UNDERSTANDING AI AND ETHICS.- 3. INFORMATION SECURITY AND DATA PRIVACY LANDSCAPE.- 4. AI FOR THREAT DETECTION AND PREVENTION.- 5. PRIVACY-PRESERVING AI TECHNIQUES.- 6. DATA PROTECTION AND COMPLIANCE.- 7. SECURING AI MODELS.- 8. CASE STUDIES.- 9. AI IN DATA PRIVACY AND ETHICS.- 10. AI AND DATA SECURITY.- 11. BALANCE BETWEEN SECURITY AND PRIVACY.- 12. BEST PRACTICES AND RECOMMENDATIONS.- 13. FUTURE TRENDS AND CHALLENGES.
1. INTRODUCTION.- 2. UNDERSTANDING AI AND ETHICS.- 3. INFORMATION SECURITY AND DATA PRIVACY LANDSCAPE.- 4. AI FOR THREAT DETECTION AND PREVENTION.- 5. PRIVACY-PRESERVING AI TECHNIQUES.- 6. DATA PROTECTION AND COMPLIANCE.- 7. SECURING AI MODELS.- 8. CASE STUDIES.- 9. AI IN DATA PRIVACY AND ETHICS.- 10. AI AND DATA SECURITY.- 11. BALANCE BETWEEN SECURITY AND PRIVACY.- 12. BEST PRACTICES AND RECOMMENDATIONS.- 13. FUTURE TRENDS AND CHALLENGES.
1. INTRODUCTION.- 2. UNDERSTANDING AI AND ETHICS.- 3. INFORMATION SECURITY AND DATA PRIVACY LANDSCAPE.- 4. AI FOR THREAT DETECTION AND PREVENTION.- 5. PRIVACY-PRESERVING AI TECHNIQUES.- 6. DATA PROTECTION AND COMPLIANCE.- 7. SECURING AI MODELS.- 8. CASE STUDIES.- 9. AI IN DATA PRIVACY AND ETHICS.- 10. AI AND DATA SECURITY.- 11. BALANCE BETWEEN SECURITY AND PRIVACY.- 12. BEST PRACTICES AND RECOMMENDATIONS.- 13. FUTURE TRENDS AND CHALLENGES.
1. INTRODUCTION.- 2. UNDERSTANDING AI AND ETHICS.- 3. INFORMATION SECURITY AND DATA PRIVACY LANDSCAPE.- 4. AI FOR THREAT DETECTION AND PREVENTION.- 5. PRIVACY-PRESERVING AI TECHNIQUES.- 6. DATA PROTECTION AND COMPLIANCE.- 7. SECURING AI MODELS.- 8. CASE STUDIES.- 9. AI IN DATA PRIVACY AND ETHICS.- 10. AI AND DATA SECURITY.- 11. BALANCE BETWEEN SECURITY AND PRIVACY.- 12. BEST PRACTICES AND RECOMMENDATIONS.- 13. FUTURE TRENDS AND CHALLENGES.
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