ScienceSDS: A Novel Software Defined Security Framework for Large-scale Data-intensive Science

Deepak Nadig Anantha, Byrav Ramamurthy
March 2017
Cite DOI URL

Abstract

Experimental science workflows from projects such as Compact Muon Solenoid (CMS) and Laser Interferometer Gravitational Wave Observatory (LIGO) are characterized by data-intensive computational tasks over large datasets transferred over encrypted channels. The Science DMZ approach to network design favors lossless packet forwarding through a separate isolated network over secure lossy forwarding through stateful packet processors (e.g. firewalls). We propose ScienceSDS, a novel software defined security framework for securely monitoring large-scale science datasets over a software defined networking and network functions virtualization (SDN/NFV) infrastructure.

Type
Conference paper
Publication
Proceedings of the ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization
Data-Intensive Science Service Function Chaining Software Defined Security
Byrav Ramamurthy
Byrav Ramamurthy
Professor & PI

My research areas include optical and wireless networks, peer-to-peer networks for multimedia streaming, network security and telecommunications. My research work is supported by the U.S. National Science Foundation, U.S. Department of Energy, U.S. Department of Agriculture, NASA, AT&T Corporation, Agilent Tech., Ciena, HP and OPNET Inc.