Fetching the paper…
Reading the bibliography…
The purpose of the automatic dependent surveillance broadcast (ADS-B) technology is to serve as a replacement for the current radar-based, air traffic control systems.
Map projections used by the US Geological Survey
John Parr Snyder. 1982 · 1982
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004 · 2004
Earlier work this paper cites.
Methods to provide system-wide ADS-B back-up, validation and security. In 25th Digital Avionics Systems Conference, 2006 IEEE/AIAA . IEEE, 1–7
A Smith, R Cassell, T Breen, R Hulstrom, and C Evers. 2006 · 2006
Earlier work this paper cites.
An integrated environment for mobile robot navigation based on CNN images processing. In Proceedings of the 11th WSEAS International Conference on SYSTEMS , Agios Nicolaos (Ed.), Vol. 5117. Crete, Greece, ISSN, 81–86
I Gavrilut, V Tiponut, and A Gacsádi. 2007 · 2007
Earlier work this paper cites.
A data authentication solution of ADS-B system based on x. 509 certificate. In 27th International Congress of the Aeronautical Sciences, ICAS . 1–6
Ziliang Feng, Weijun Pan, and Yang Wang. 2010 · 2010
Earlier work this paper cites.
ADS-B Implementation and Operations Guidance Document
W Blythe, H Anderson, and N King. 2011 · 2011
Earlier work this paper cites.
Security analysis of the ADS-B implementation in the next generation air transportation system
Donald McCallie, Jonathan Butts, and Robert Mills. 2011 · 2011
Earlier work this paper cites.
Detection of masses in mammogram images using CNN, geostatistic functions and SVM
Wener Borges Sampaio, Edgar Moraes Diniz, Aristófanes Corrêa Silva, Anselmo Cardoso De Paiva, and Marcelo Gattass. 2011 · 2011
Earlier work this paper cites.
Short paper: reactive jamming in wireless networks: how realistic is the threat?. In Proceedings of the fourth ACM conference on Wireless network security . ACM, 47–52
Matthias Wilhelm, Ivan Martinovic, Jens B Schmitt, and Vincent Lenders. 2011 · 2011
Earlier work this paper cites.
Ghost in the Air (Traffic): On insecurity of ADS-B protocol and practical attacks on ADS-B devices
Andrei Costin and Aurélien Francillon. 2012 · 2012
Earlier work this paper cites.
Enhancing the security of aircraft surveillance in the next generation air traffic control system
Cindy Finke, Jonathan Butts, Robert Mills, and Michael Grimaila. 2013 · 2013
Earlier work this paper cites.
Experimental analysis of attacks on next generation air traffic communication. In International Conference on Applied Cryptography and Network Security . Springer, 253–271
Matthias Schäfer, Vincent Lenders, and Ivan Martinovic. 2013 · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Verifying ADS-B navigation information through Doppler shift measurements. In Digital Avionics Systems Conference (DASC), 2015 IEEE/AIAA 34th . IEEE, 4A2–1
Nirnimesh Ghose and Loukas Lazos. 2015 · 2015
Cited alongside, same era.
Key distribution mechanism in secure ADS-B networks. In Integrated Communication, Navigation, and Surveillance Conference (ICNS), 2015 . IEEE, P3–1
Thabet Kacem, Duminda Wijesekera, Paulo Costa, Jeronymo Carvalho, Márcio Monteiro, and Alexandre Barreto. 2015 · 2015
Cited alongside, same era.
Secure track verification. In Security and Privacy (SP), 2015 IEEE Symposium on . IEEE, 199–213
Matthias Schäfer, Vincent Lenders, and Jens Schmitt. 2015 · 2015
Cited alongside, same era.
Intrusion detection for airborne communication using phy-layer information. In International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment . Springer, 67–77
Martin Strohmeier and Vincent Lenders. 2015 · 2015
Cited alongside, same era.
On the security of the automatic dependent surveillance-broadcast protocol
A unified approach to interpreting model predictions. In Advances in Neural Information Processing Systems . 4765–4774
Scott M Lundberg and Su-In Lee. 2017 · 2017
Later among the works it cites.
Learning important features through propagating activation differences. In Proceedings of the 34th International Conference on Machine Learning-Volume 70 . JMLR. org, 3145–3153
Avanti Shrikumar, Peyton Greenside, and Anshul Kundaje. 2017 · 2017
Later among the works it cites.
Using LSTM encoder-decoder algorithm for detecting anomalous ADS-B messages
Edan Habler and Asaf Shabtai. 2018 · 2018
Later among the works it cites.
Detecting cyber attacks in industrial control systems using convolutional neural networks. In Proceedings of the 2018 Workshop on Cyber-Physical Systems Security and PrivaCy . ACM, 72–83
Moshe Kravchik and Asaf Shabtai. 2018 · 2018
Later among the works it cites.
A k-NN-based Localization Approach for Crowdsourced Air Traffic Communication Networks
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Martin Strohmeier, Vincent Lenders, and Ivan Martinovic. 2015b · 2015
Cited alongside, same era.
Opensky: A swiss army knife for air traffic security research. In 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC) . IEEE, 4A1–1
Martin Strohmeier, Ivan Martinovic, Markus Fuchs, Matthias Schäfer, and Vincent Lenders. 2015c · 2015
Cited alongside, same era.
Convolutional LSTM network: A machine learning approach for precipitation nowcasting. In Advances in neural information processing systems . 802–810
SHI Xingjian, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo. 2015 · 2015
Cited alongside, same era.
Unsupervised learning for physical interaction through video prediction. In Advances in neural information processing systems . 64–72
Chelsea Finn, Ian Goodfellow, and Sergey Levine. 2016 · 2016
Cited alongside, same era.
Anomaly detection in video using predictive convolutional long short-term memory networks
Jefferson Ryan Medel and Andreas Savakis. 2016 · 2016
Cited alongside, same era.
Why should i trust you?: Explaining the predictions of any classifier. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining . ACM, 1135–1144
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016 · 2016
Cited alongside, same era.
Secure Motion Verification using the Doppler Effect. In Proceedings of the 9th ACM Conference on Security & Privacy in Wireless and Mobile Networks . ACM, 135–145
Matthias Schäfer, Patrick Leu, Vincent Lenders, and Jens Schmitt. 2016 · 2016
Cited alongside, same era.
Large-Scale Flight Phase Identification from ADS-B Data Using Machine Learning Methods. In 7th International Conference on Research in Air Transportation
Junzi Sun, Joost Ellerbroek, and Jacco Hoekstra. 2016 · 2016
Cited alongside, same era.
Martin Strohmeier, Ivan Martinovic, and Vincent Lenders. 2018a · 2018
Later among the works it cites.
The Real First Class? Inferring Confidential Corporate Mergers and Government Relations from Air Traffic Communication. In 2018 IEEE European Symposium on Security and Privacy (EuroS&P) . IEEE, 107–121
Martin Strohmeier, Matthew Smith, Vincent Lenders, and Ivan Martinovic. 2018b · 2018
Later among the works it cites.
Explaining Anomalies Detected by Autoencoders Using SHAP
Liat Antwarg, Bracha Shapira, and Lior Rokach. 2019 · 2019
Closest in time.
ex2: a framework for interactive anomaly detection
Ignacio Arnaldo, K Veeramachaneni, and M Lam. 2019 · 2019
Closest in time.
Security of ADS-B: Attack Scenarios
Kayvan Faghih Mirzaei, Bruno Pessanha de Carvalho, and Patrick Pschorn. 2019 · 2019
Closest in time.
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran, Kian Hsiang Low, and Mun Choon Chan. 2019 · 2019
Closest in time.
Multidevice False Data Injection Attack Models of ADS-B Multilateration Systems
Fute Shang, Buhong Wang, Fuhu Yan, and Tengyao Li. 2019 · 2019
Closest in time.
Ensemble machine learning models for aviation incident risk prediction
Xiaoge Zhang and Sankaran Mahadevan. 2019 · 2019
Closest in time.
Show, attend and tell: Neural image caption generation with visual attention. In International conference on machine learning . 2048–2057
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio. 2015 · 2057
Closest in time.