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Titlebook: Digital Forensics and Cyber Crime; 13th EAI Internation Sanjay Goel,Pavel Gladyshev,Daryl Johnson Conference proceedings 2023 ICST Institut

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發(fā)表于 2025-3-23 13:32:24 | 只看該作者
https://doi.org/10.1007/978-981-15-2529-2e their use also became increasingly popular..This also intensified the involvement of these cryptowallet apps in criminal activities such as ransom requests, money laundering, and transactions on dark markets. From a digital forensics point of view, it is crucial to have tools and reliable approach
12#
發(fā)表于 2025-3-23 17:15:23 | 只看該作者
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發(fā)表于 2025-3-23 20:08:28 | 只看該作者
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發(fā)表于 2025-3-23 23:09:44 | 只看該作者
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發(fā)表于 2025-3-24 04:23:24 | 只看該作者
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發(fā)表于 2025-3-24 07:05:36 | 只看該作者
17#
發(fā)表于 2025-3-24 13:48:17 | 只看該作者
Image-to-Image Translation Generative Adversarial Networks for Video Source Camera Falsificationent of accurate digital forensic techniques which require not only the confirmation of the data integrity but also the verification of its origin source. To this end, machine and/or deep learning techniques are widely being employed within forensics tools. Nevertheless, while these techniques became
18#
發(fā)表于 2025-3-24 16:43:56 | 只看該作者
19#
發(fā)表于 2025-3-24 22:04:47 | 只看該作者
Can Image Watermarking Efficiently Protect Deep-Learning-Based Image Classifiers? – A Preliminary SeNNs) have successfully helped boost business efficiency and reduce costs. To protect the intellectual property (IP) of DNN classifiers, a blind-watermarking-based technique that opens “backdoors” through image steganography has been proposed. However, it is yet to explore whether this approach can e
20#
發(fā)表于 2025-3-25 01:39:53 | 只看該作者
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