ADS-B spoofing attack detection method based on LSTM

The open and shared nature of the Automatic Dependent Surveillance Broadcast (ADS-B) protocol makes its messages extremely vulnerable to various security threats, such as jamming, modification, and injection. This paper proposes a long short-term memory (LSTM)-based ADS-B spoofing attack detection m...

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Bibliographic Details
Published in:EURASIP journal on wireless communications and networking 2020-08, Vol.2020 (1), p.1-12, Article 160
Main Authors: Wang, Jing, Zou, Yunkai, Ding, Jianli
Format: Article
Language:English
Subjects:
ADS-B
ADS-B system
Attack detection
Communications Engineering
Edge
Engineering
Fog
Human-centered Computing in Cloud
Information Systems Applications (incl.Internet)
Jamming
LSTM
Messages
Networks
Predictions
Security
Security threat
Signal,Image and Speech Processing
Sliding window
Spoofing
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Summary:The open and shared nature of the Automatic Dependent Surveillance Broadcast (ADS-B) protocol makes its messages extremely vulnerable to various security threats, such as jamming, modification, and injection. This paper proposes a long short-term memory (LSTM)-based ADS-B spoofing attack detection method from the perspective of data. First, the message sequence is preprocessed in the form of a sliding window, and then, an LSTM network is used to perform prediction training on the windows. Finally, the residual set of predicted values and true values is calculated to set a threshold. As a result, we can detect a spoofing attack and further identify which feature was attacked. Experiments show that this method can effectively detect 10 different kinds of simulated manipulated ADS-B messages without further increasing the complexity of airborne applications. Therefore, the method can respond well to the security threats suffered by the ADS-B system.
ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-020-01756-8