Adversarial Multimedia Forensics / Advances in Information Security Bd.104 (PDF)
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This book explores various aspects of digital forensics, security and machine learning, while offering valuable insights into the ever-evolving landscape of multimedia forensics and data security. This book's content can be summarized in two main areas. The first area of this book primarily addresses techniques and methodologies related to digital image forensics. It discusses advanced techniques for image manipulation detection, including the use of deep learning architectures to generate and manipulate synthetic satellite images. This book also explores methods for face recognition under adverse conditions and the importance of forensics in criminal investigations. Additionally, the book highlights anti-forensic measures applied to photos and videos, focusing on their effectiveness and trade-offs.
The second area of this book focuses on the broader landscape of security, including the detection of synthetic human voices, secure deep neural networks (DNNs) and federated learning in the context of machine learning security. It investigates novel methods for detecting synthetic human voices using neural vocoder artifacts, and it explores the vulnerabilities and security challenges of federated learning in the face of adversarial attacks. Furthermore, this book delves into the realms of linguistic steganography and steganalysis, discussing the evolving techniques that utilize deep learning and natural language processing to enhance payload and detection accuracy.
Overall, this book provides a comprehensive overview of the ever-evolving field of digital forensics and security, making it an invaluable resource for researchers and students interested in image forensics, machine learning security and information protection. It equips readers with the latest knowledge and tools to address the complex challenges posed by the digital landscape. Professionals working in this related field will also find this book to be a valuable resource.
Dr.Kassem Kallas is a seasoned Research Scientist with expertise in the fields of Machine Learning (ML) and Artificial Intelligence (AI). He has a wealth of experience in applying these concepts to real-world problems. Dr. Kallas earned his Ph.D. in
Dr. Alireza Jolfaei is an Associate Professor in Cybersecurity and Networking in the College of Science and Engineering at Flinders University. He is a Senior Member of the IEEE and a Distinguished Speaker of the ACM on the topic of Cybersecurity. He has previously been a faculty member with Macquarie University and Federation University in Australia, and Temple University in the USA. He received a Ph.D. degree in Applied Cryptography from Griffith University, Gold Coast, Australia. His main research interest is in Cyber-Physical Systems Security, where he investigates the hidden interdependencies in industrial communication protocols and aims to provide fundamentally new methods for security-aware modelling, analysis and design of safety-critical cyber-physical systems in the presence of cyber-adversaries. He has been a chief investigator of several internal and external grants with a total amount exceeding $2,6 million. He successfully supervised eight HDR students to completion. He received the prestigious IEEE Australian Council award for his research paper published in the IEEE Transactions on Information Forensics and Security.
- 2024, 2024, 284 Seiten, Englisch
- Herausgegeben: Ehsan Nowroozi, Kassem Kallas, Alireza Jolfaei
- Verlag: Springer International Publishing
- ISBN-10: 3031498038
- ISBN-13: 9783031498039
- Erscheinungsdatum: 04.03.2024
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- Größe: 10 MB
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