Titlebook: Adversarial Multimedia Forensics; Ehsan Nowroozi,Kassem Kallas,Alireza Jolfaei Book 2024 The Editor(s) (if applicable) and The Author(s),

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https://doi.org/10.1007/978-3-031-49803-9Adversarial Attacks; DeepFake Detection; Multimedia Forensics; Digital Forensics; Image Forensics; Video

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CRUMB

Model Poisoning Attack Against Federated Learning with Adaptive Aggregation, a new era of collaborative data-driven insights. However, the growing adoption of FL brings forth the need to scrutinize its vulnerabilities and security challenges, particularly concerning adversarial attacks. This book chapter delves into the intricate realm of FL’s susceptibility to adversarial

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ORBIT

Refined GAN-Based Attack Against Image Splicing Detection and Localization Algorithms,hniques. These algorithms utilize Siamese neural networks to detect and localize spliced contents by identifying inconsistencies in an image’s forensic traces. At the same time, deep learning has also enabled the researchers to develop new types of anti-forensic attack that can fool forensic algorit

法律的瑕疵

Generative Adversarial Networks for Artificial Satellite Image Creation and Manipulation,deep learning architectures (DL),Synthetic satellite images offer a wide range of potential applications, including the generation of massive, labeled datasets for artificial intelligence (AI) applications, manipulated image detection, and natural disaster monitoring and detection. Although deep lea

Lament

Domain Specific Information Based Learning for Facial Image Forensics,cs is one of the sub fields of multimedia forensics which involves any kind of digital images such as face, fingerprint etc. Security systems are one of the most sophisticated systems to protect assets and privacy in recent years. The demand for fast, accurate identification and authentication is in

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