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Advanced Intrusion Prevention for Geographically Dispersed Higher Education Cloud Networks

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Online Engineering & Internet of Things

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 22))

Abstract

We present the design and implementation of a novel cybersecurity architecture for a Linux community public cloud supporting education and research. The approach combines first packet authentication and transport layer access control gateways to block fingerprinting of key network resources. Experimental results are presented for two interconnected data centers in New York. We show that this approach can block denial of service attacks and network scanners, and provide geolocation attribution based on a syslog classifier.

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References

  1. McCarthy, S.: Pivot Table: U.S. Education IT Spending Guide, version 1, 2013–2018. IDC publication GI255747, April 2015. http://www.idc.com/getdoc.jsp?containerId=GI255747

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Acknowledgments

The authors gratefully acknowledge support of the National Science Foundation grant Cloud Computing – Data, Networking, Innovation (CC-DNI), area 4, 15-535, also known as “SecureCloud”.

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Correspondence to C. DeCusatis .

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DeCusatis, C., Liengtiraphan, P., Sager, A. (2018). Advanced Intrusion Prevention for Geographically Dispersed Higher Education Cloud Networks. In: Auer, M., Zutin, D. (eds) Online Engineering & Internet of Things. Lecture Notes in Networks and Systems, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-64352-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-64352-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64351-9

  • Online ISBN: 978-3-319-64352-6

  • eBook Packages: EngineeringEngineering (R0)

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