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Twin Auto-Encoder Model for Learning Separable Representation in Cyberattack Detection
March 26, 2024, 4:10 a.m. | Phai Vu Dinh, Quang Uy Nguyen, Thai Hoang Dinh, Diep N. Nguyen, Bao Son Pham, Eryk Dutkiewicz
cs.CR updates on arXiv.org arxiv.org
Abstract: Representation Learning (RL) plays a pivotal role in the success of many problems including cyberattack detection. Most of the RL methods for cyberattack detection are based on the latent vector of Auto-Encoder (AE) models. An AE transforms raw data into a new latent representation that better exposes the underlying characteristics of the input data. Thus, it is very useful for identifying cyberattacks. However, due to the heterogeneity and sophistication of cyberattacks, the representation of AEs …
arxiv auto cs.ai cs.cr cs.lg cyberattack data detection problems representation role twin
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