SoK of Machine Learning and Deep Learning Based Anomaly Detection Methods for Automatic Dependent Surveillance- Broadcast
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee-Inst Electrical Electronics Engineers Inc
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper focuses on the vulnerabilities of ADS-B, one of the avionics systems, and the countermeasures taken against these vulnerabilities proposed in the literature. Among the proposed countermeasures against the vulnerabilities of ADS-B, anomaly detection methods based on machine learning and deep learning algorithms were analyzed in detail. The advantages and disadvantages of using an anomaly detection system on ADS-B data are investigated. Thanks to advances in machine learning and deep learning over the last decade, it has become more appropriate to use anomaly detection systems to detect anomalies in ADS-B systems. To the best of our knowledge, this is the first survey to focus on studies using machine learning and deep learning algorithms for ADS-B security. In this context, this study addresses research on this topic from different perspectives, draws a road map for future research, and searches for five research questions related to machine learning and deep learning algorithms used in anomaly detection systems.
Açıklama
Anahtar Kelimeler
Deep Learning, Aircraft, Anomaly Detection, Surveys, Intrusion Detection, Databases, Computer Security, Machine Learning, Ads-B, Anomaly Based Intrusion Detection System, Anomaly Detection System, Cyber Security, Avionics Security, Deep Learning, Ids, Intrusion Detection System, Machine Learning
Kaynak
Ieee Access
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
12
