Artificial Intelligence
Data and Model Safety
$536.34
- Paperback
386 pages
- Release Date
27 August 2025
Summary
This book delves into the critical intersection of Artificial Intelligence (AI), data, and security, exploring the inherent risks and sophisticated attacks that arise from these powerful technologies. It provides a comprehensive overview of the evolving threat landscape, examining how AI can be exploited for malicious purposes and the vulnerabilities created by the vast amounts of data we generate and rely upon.
Crucially, the book also focuses on the defensive strategies and cutting-…
Book Details
| ISBN-13: | 9780443248405 |
|---|---|
| ISBN-10: | 0443248400 |
| Author: | Yu-Gang Jiang, Xingjun Ma, Zuxuan Wu |
| Publisher: | Elsevier - Health Sciences Division |
| Imprint: | Elsevier - Health Sciences Division |
| Format: | Paperback |
| Number of Pages: | 386 |
| Release Date: | 27 August 2025 |
| Weight: | 450g |
| Dimensions: | 152mm x 229mm |
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Yu-Gang Jiang
Professor Yu-Gang Jiang is based at Fudan University, PR China. He is primarily engaged in scientific research in artificial intelligence, multimedia information processing, and secure and trustworthy machine learning. He has published over 100 papers in top international journals and conferences in these domains. In recent years, he has achieved multiple innovative results in artificial intelligence security, such as proposing the first black-box video adversarial sample generation method and the first data poisoning and backdoor attack methods for video recognition models.
Dr Xingjun Ma is an associate professor in the School of Computer Science and Technology, Fudan University, PR China. He obtained his doctoral degree from The University of Melbourne in Australia in 2019. He has previously worked as a research fellow at The University of Melbourne and as a lecturer at Deakin University. His research focuses on trustworthy machine learning, specifically the security, robustness, interpretability, privacy, and fairness of machine learning data, algorithms, and models. He has published over 50 papers in top international conferences and journals and holds two international patents.
Dr Zuxuan Wu is currently an assistant professor at the School of Computer Science and Technology, Fudan University, China. In 2020, he obtained his doctoral degree from the University of Maryland in the US. His main research interests include computer vision, deep learning, and multimedia content analysis. He has been awarded the AI 2000 Most Influential Scholars Award in 2022, and the Microsoft Research Ph.D. Fellowship in 2019, and the Snap Ph.D. Fellowship in 2017.
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