TY - GEN
T1 - Implementing Autoencoder Compression to Intrusion Detection System
AU - Krisna Pamungkas, I. Gede Agung
AU - Ahmad, Tohari
AU - Ijtihadie, Royyana Muslim
AU - Shiddiqi, Ary Mazharuddin
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Intrusion Detection System helps catch dangerous incoming packets to a computer network. Despite its substantial role, achieving a high-performance system is still challenging, which may cause insecure whole computer networks. Therefore, a reliable system, which can recognize such threatening attacks, is required. Inspired by previous studies, in this research, we take the Autoencoder to extract and reduce the packet’s features and then analyze the results using the Softmax classifier. Furthermore, we remove dropouts and increase the number of batches. The experimental results show that this approach can improve the system's performance. Nevertheless, some works should still be carried out in the future to increase the system’s reliability.
AB - Intrusion Detection System helps catch dangerous incoming packets to a computer network. Despite its substantial role, achieving a high-performance system is still challenging, which may cause insecure whole computer networks. Therefore, a reliable system, which can recognize such threatening attacks, is required. Inspired by previous studies, in this research, we take the Autoencoder to extract and reduce the packet’s features and then analyze the results using the Softmax classifier. Furthermore, we remove dropouts and increase the number of batches. The experimental results show that this approach can improve the system's performance. Nevertheless, some works should still be carried out in the future to increase the system’s reliability.
KW - Autoencoder
KW - Feature Extraction
KW - IDS
KW - Intrusion
KW - Network Infrastructure
KW - Network Security
UR - http://www.scopus.com/inward/record.url?scp=85163335565&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-27409-1_113
DO - 10.1007/978-3-031-27409-1_113
M3 - Conference contribution
AN - SCOPUS:85163335565
SN - 9783031274084
T3 - Lecture Notes in Networks and Systems
SP - 1235
EP - 1243
BT - Hybrid Intelligent Systems - 22nd International Conference on Hybrid Intelligent Systems HIS 2022
A2 - Abraham, Ajith
A2 - Abraham, Ajith
A2 - Hong, Tzung-Pei
A2 - Kotecha, Ketan
A2 - Ma, Kun
A2 - Manghirmalani Mishra, Pooja
A2 - Gandhi, Niketa
PB - Springer Science and Business Media Deutschland GmbH
T2 - 22nd International Conference on Hybrid Intelligent Systems, HIS 2022 and the 18th International Conference on Information Assurance and Security, IAS 2022
Y2 - 13 December 2022 through 15 December 2022
ER -