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Titlebook: Information Security Applications; 22nd International C Hyoungshick Kim Conference proceedings 2021 Springer Nature Switzerland AG 2021 AI

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31#
發(fā)表于 2025-3-27 00:10:34 | 只看該作者
978-3-030-89431-3Springer Nature Switzerland AG 2021
32#
發(fā)表于 2025-3-27 02:40:03 | 只看該作者
Information Security Applications978-3-030-89432-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
33#
發(fā)表于 2025-3-27 06:44:13 | 只看該作者
34#
發(fā)表于 2025-3-27 13:29:56 | 只看該作者
35#
發(fā)表于 2025-3-27 15:42:24 | 只看該作者
0302-9743 ich took place on Jeju Island, South Korea, during August 2021.?The 23 papers included in this book were carefully reviewed and selected from 66 submissions. They were organized in topical sections as follows: machine learning security; cryptography; hardware security; and application security..978-
36#
發(fā)表于 2025-3-27 20:17:05 | 只看該作者
0302-9743 ssions. They were organized in topical sections as follows: machine learning security; cryptography; hardware security; and application security..978-3-030-89431-3978-3-030-89432-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
37#
發(fā)表于 2025-3-28 00:38:13 | 只看該作者
Pattern Matching over Encrypted Data with a Short Ciphertextxpensive pairing computations proportional to the ciphertext length. Our work reduces the ciphertext size by up?to 50% of the state-of-art scheme in this research domain while maintaining the same level of search efficiency.
38#
發(fā)表于 2025-3-28 02:16:06 | 只看該作者
Efficient Adaptation of TFHE for High End-to-End Throughputstrapping procedure to operate the same binary circuits on the server. Finally, without any additional public keys, we propose a new Keyswitching algorithm that we call ., which enables even the server to pack multiple messages, thereby achieving high end-to-end throughput for TFHE.
39#
發(fā)表于 2025-3-28 08:40:05 | 只看該作者
40#
發(fā)表于 2025-3-28 11:19:05 | 只看該作者
Echo-Guard: Acoustic-Based Anomaly Detection System for Smart Manufacturing Environmentspectrogram images are further classified using CNN to detect anomalies in machine motion sounds. Our evaluation, conducted in a smart factory environment, shows that Echo-Guard is effective, achieving 99.44% accuracy, confirming the possibility that machine motion sounds can be utilized to detect anomalies.
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