Work

Intrusion Detection for ARINC-429: A Hybrid FFT and Unsupervised Learning Approach

Year: 2025

Type: conference-paper

Source: Integrated Communications, Navigation and Surveillance Conference (ICNS)

DOI: 10.1109/icns65417.2025.10976795

Authors: İsa Can Babir, Mustafa Evcil, Zaliha Yüce Tok, Mehmet Atınç Gökyer, Yiğit Emir İşıkçı, Sedat Akleylek

Institutions: Aselsan (Turkey), University of Tartu

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4410117157

FWCI: 5.325

Cites: 9

Cited by: 4

Related to: 10