TY - GEN
T1 - Poster abstract
T2 - 2021 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
AU - Jeong, Hyejeong
AU - Yu, Jieun
AU - Lee, Wonjun
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A2C2088812). Wonjun Lee is the corresponding author.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/10
Y1 - 2021/5/10
N2 - Network intrusion detection is a crucial task since malicious traffic occurs every second these days. Various research has been studied in this field and shows high performance. However, most of them are conducted in a supervised manner that needs a range of labeled data but it is hard to obtain. This paper proposes a semi-supervised Generative Adversarial Networks (GAN) model for network intrusion detection that requires only 10 labeled data per each flow type. Our model is evaluated using the publicly available CICIDS-2017 dataset and outperforms other malware traffic classification models.
AB - Network intrusion detection is a crucial task since malicious traffic occurs every second these days. Various research has been studied in this field and shows high performance. However, most of them are conducted in a supervised manner that needs a range of labeled data but it is hard to obtain. This paper proposes a semi-supervised Generative Adversarial Networks (GAN) model for network intrusion detection that requires only 10 labeled data per each flow type. Our model is evaluated using the publicly available CICIDS-2017 dataset and outperforms other malware traffic classification models.
KW - Generative Adversarial Network
KW - Network Intrusion Detection
KW - Semi-supervised learning
UR - http://www.scopus.com/inward/record.url?scp=85113296166&partnerID=8YFLogxK
U2 - 10.1109/INFOCOMWKSHPS51825.2021.9484569
DO - 10.1109/INFOCOMWKSHPS51825.2021.9484569
M3 - Conference contribution
AN - SCOPUS:85113296166
T3 - IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
BT - IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 May 2021 through 12 May 2021
ER -