The software-defined networking (SDN) paradigm promises greater control and understanding of enterprise network activities, particularly for management applications that need awareness of network-wide behavior. However, the current focus on switch-based SDNs raises concerns about data-plane scalability, especially when using fine-grained flows. Further, these switch-centric approaches lack visibility into end-host and application behaviors, which are valuable when making access control decisions. In recent work, we proposed a host-based SDN in which we installed software on the end-hosts and used a centralized network control to manage the flows. This improve scalability and provided application information for use in network policy. However, that approach was not compatible with OpenFlow and had provided only conservative estimates of possible network performance. In this work, we create a high performance host-based SDN that is compatible with the OpenFlow protocol. Our approach, DeepContext, provides details about the application context to the network controller, allowing enhanced decision-making. We evaluate the performance of DeepContext, comparing it to traditional networks and Open vSwitch deployments. We further characterize the completeness of the data provided by the system and the resulting benefits.
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Contextual, flow-based access control with scalable host-based SDN techniques
Network operators can better understand their networks when armed with a detailed understanding of the network traffic and host activities. Software-defined networking (SDN) techniques have the potential to improve enterprise security, but the current techniques have well-known data plane scalability concerns and limited visibility into the host's operating context. In this work, we provide both detailed host-based context and fine-grained control of network flows by shifting the SDN agent functionality from the network infrastructure into the end-hosts. We allow network operators to write detailed network policy that can discriminate based on user and program information associated with network flows. In doing so, we find our approach scales far beyond the capabilities of OpenFlow switching hardware, allowing each host to create over 25 new flows per second with no practical bound on the number of established flows in the network.
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- Award ID(s):
- 1422180
- PAR ID:
- 10055769
- Date Published:
- Journal Name:
- IEEE International Conference on Computer Communications (INFOCOM)
- Page Range / eLocation ID:
- 1 to 9
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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