Author:
Laštovička Martin,Čeleda Pavel
Abstract
AbstractLarge-scale networks consisting of thousands of connected devices are like a living organism, constantly changing and evolving. It is very difficult for a human administrator to orient in such environment and to react to emerging security threats. With such motivation, this PhD proposal aims to find new methods for automatic identification of devices, the services they provide, their dependencies and importance. The main focus of the proposal is to find novel approaches to building cyber situational awareness in an unknown network for the purpose of computer security incident response. Our research is at the initial phase and will contribute to a PhD thesis in four years.
Publisher
Springer International Publishing
Reference11 articles.
1. Callado, A., Kamienski, C., Szabó, G., Gero, B.P., Kelner, J., Fernandes, S., Sadok, D.: A survey on internet traffic identification. IEEE Commun. Surv. Tutorials 11(3), 37–52 (2009)
2. Franke, U., Brynielsson, J.: Cyber situational awareness - a systematic review of the literature. Comput. Secur. 46, 18–31 (2014)
3. Hofstede, R., Čeleda, P., Trammell, B., Drago, I., Sadre, R., Sperotto, A., Pras, A.: Flow monitoring explained: from packet capture to data analysis with NetFlow and IPFIX. IEEE Commun. Surv. Tutorials 16(4), 2037–2064 (2014, Fourthquarter)
4. Husák, M., Čermák, M., Jirsík, T., Čeleda, P.: HTTPS traffic analysis and client identification using passive SSL/TLS fingerprinting. EURASIP J. Inf. Secur. 2016(6), 1–14 (2016)
5. Kim, A., Kang, M.H.: Determining asset criticality for cyber defense. Technical report, Naval Research Lab, Washington DC (2011)
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