Privacy-preserving knowledge transfer for intrusion detection with federated deep autoencoding gaussian mixture model
Knowledge transfer is critical in making use of data from multi-source domains, but most existing techniques are not privacy-preserving. Nowadays, data leakage, together with the advancement of big-data-driven Artificial Intelligence, has raised huge concerns over data security. The neglect of priva...
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Main Authors: | Chen, Yang, Zhang, Junzhe, Yeo, Chai Kiat |
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Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/163890 |
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Institution: | Nanyang Technological University |
Language: | English |
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