DronLomaly: Runtime detection of anomalous drone behaviors via log analysis and deep learning
Drones are increasingly popular and getting used in a variety of missions such as area surveillance, pipeline inspection, cinematography, etc. While the drone is conducting a mission, anomalies such as sensor fault, actuator fault, configuration errors, bugs in controller program, remote cyber- atta...
Saved in:
Main Authors: | SHAR, Lwin Khin, MINN, Wei, TA, Nguyen Binh Duong, FAN, Jianli, JIANG, Lingxiao, LIM, Daniel Wai Kiat |
---|---|
格式: | text |
語言: | English |
出版: |
Institutional Knowledge at Singapore Management University
2022
|
主題: | |
在線閱讀: | https://ink.library.smu.edu.sg/sis_research/7545 https://ink.library.smu.edu.sg/context/sis_research/article/8548/viewcontent/Drone_Log_Anomaly_Detection_camera_ready.pdf |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Singapore Management University |
語言: | English |
相似書籍
-
DronLomaly: Runtime log-based anomaly detector for DJI drones
由: MINN, Wei, et al.
出版: (2024) -
Fuzzing drones for anomaly detection: A systematic literature review
由: MALVIYA, Vikas Kumar, et al.
出版: (2025) -
Leveraging large language models and BERT for log parsing and anomaly detection
由: Zhou, Yihan, et al.
出版: (2024) -
A Dynamic Rule Creation Based Anomaly Detection Method for Identifying Security Breaches in Log Records
由: Breier, Jakub, et al.
出版: (2016) -
Drone perching control
由: Yan, Daryl ZhenYu
出版: (2024)