Logo
User: Guest  Login
Authors:
Wang, Weixing; Yang, Haojin; Meinel, Christoph; Özkan, Yagiz Hasan; Bermudez Serna, Cristian; Mas-Machuca, Carmen 
Document type:
Konferenzbeitrag / Conference Paper 
Title:
Feature Distribution Shift Mitigation with Contrastive Pretraining for Intrusion Detection 
Collection editors:
IEEE 
Conference title:
Network Traffic Measurement and Analysis Conference 
Year of conference:
2024 
Year:
2024 
Language:
Englisch 
Subject:
Communication Networks 
Abstract:
In recent years, there has been a growing interest in using Machine Learning (ML), especially Deep Learning (DL) to solve Network Intrusion Detection (NID) problems. However, the feature distribution shift problem remains a difficulty, because the change in features’ distributions over time negatively impacts the model’s performance. As one promising solution, model pretraining has emerged as a novel training paradigm, which brings robustness against feature distribution shift and has proven to...    »
 
Department:
Fakultät für Elektrotechnik und Informationstechnik 
Institute:
EIT 3 - Institut für Informationstechnik 
Chair:
Mas-Machuca, Carmen 
Open Access yes or no?:
Ja / Yes 
Miscellaneous:
Voraufnahme