IEEE Computer Society

发表于：IEEE Multimedia · 年份：2018 · DOI：10.1109/mitp.2018.2889661

2. J. Giraldo, E. Sarkar, A. A. Cardenas, M. Maniatakos, and M. Kantarcioglu, “Security and privacy in cyber-physical systems: A survey of surveys,” IEEE Des. Test., vol. 34, no. 4, pp. 7–17, 2017. doi: 10.1109/ MDAT.2017.2709310. 3. N. Papernot, P. McDaniel, S. Jha, M. Fredrikson, Z. B. Celik, and A. Swami, “The limitations of deep learning in adversarial settings,” in Proc. 2016 IEEE European Symp. Security and Privacy (EuroS&P), Saarbrucken, pp. 372–387. doi: 10.1109/ EuroSP.2016.36. 4. A. L. Buczak and E. Guven, “A survey of data mining and machine learning methods for cyber security intrusion detection,” IEEE Commun. Surveys Tuts., vol. 18, no. 2, pp. 1153–1176, 2016. doi: 10.1109/ COMST.2015.2494502. 5. K. Eykholt et al., “Robust physical-world attacks on deep learning visual classification,” in Proc. 2018 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, UT, June 18–22, 2018, pp. 1625–1634. doi: 10.1109/ CVPR.2018.00175. 6. J. Sztipanovits et al., “Toward a science of cyber–physical system integration,” Proc. IEEE, vol. 100, no. 1, pp. 29–44, 2012. doi: 10.1109/ JPROC.2011.2161529. 7. X. Koutsoukos et al., “SURE: A modeling and simulation integration platform for evaluation of secure and resilient cyber–physical systems,” Proc. IEEE, vol. 106, no. 1, pp. 93–112, 2018. doi: 10.1109/ JPROC.2017.2731741. 8. IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA): Framework and Rules, IEEE Standard 1516, 2010. 9. J. Sztip...