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The software-defined networking (SDN) paradigm offers significant flexibility for network operators. However, the SDN community has focused on switch-based implementations, which pose several challenges. First, some may require significant hardware costs to upgrade a network. Further, fine-grained flow control in a switch-based SDN results in well-known, fundamental scalability limitations. These challenges may limit the reach of SDN technologies. In this work, we explore the extent to which host-based SDN agents can achieve feature parity with switch-based SDNs. Prior work has shown the potential of host-based SDNs for security and access control. Our study finds that with appropriate preparation, a host-based agent offers the same capabilities of switch-based SDNs in the remaining key area of traffic engineering, even in a legacy managed-switch network. We find the approach offers comparable performance to switch-based SDNs while eliminating the flow table scalability and cost concerns of switch-based SDN deployments. 

Endpoint sensors play an important role in an organization's network defense. However, endpoint sensors may be disabled or sabotaged if an adversary gains root-level access to the endpoint running the sensor. While traditional sensors cannot reliably defend against such compromises, this work explores an approach to detect these compromises in applications where multiple sensors can be correlated. We focus on the OpenFlow protocol and show that endpoint sensor data can be corroborated using a remote endpoint's sensor data or that of in-network sensors, like an OpenFlow switch. The approach allows end-to-end round trips of less than 20ms for around 90% of flows, which includes all flow elevation and processing overheads. In addition, the approach can detect flows from compromised nodes if there is a single uncompromised sensor on the network path. This approach allows defenders to quickly identify and quarantine nodes with compromised endpoint sensors. 

Residential networks are home to increasingly diverse devices, including embedded devices that are part of the Internet of Things phenomenon, leading to new management and security challenges. However, current residential solutions that rely on customer premises equipment (CPE), which often remains deployed in homes for years without updates or maintenance, are not evolving to keep up with these emerging demands. Recently, researchers have proposed to outsource the tasks of managing and securing residential networks to cloud-based security services by leveraging software-defined networking (SDN). However, the use of cloud-based infrastructure may have performance implications. In this paper, we measure the performance impact and perception of a residential SDN using a cloud-based controller through two measurement studies. First, we recruit 270 residential users located across the United States to measure residential latency to cloud providers. Our measurements suggest the cloud controller architecture provides 90% of end-users with acceptable performance with judiciously selected public cloud locations. When evaluating web page loading times of popular domains, which are particularly latency-sensitive, we found an increase of a few seconds at the median. However, optimizations could reduce this overhead for top websites in practice. 

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. 

Residential networks pose a unique challenge for security since they are operated by end-users that may not have security expertise. Residential networks are also home to devices that may have lackluster security protections, such as Internet of Things (IoT) devices, which may introduce vulnerabilities. In this work, we introduce TLSDeputy, a middlebox-based system to protect residential networks from connections to inauthentic TLS servers. By combining the approach with OpenFlow, a popular software-defined networking protocol, we show that we can effectively provide residential network-wide protections across diverse devices with minimal performance overheads. 

While enterprise networks follow best practices and security measures, residential networks often lack these protections. Home networks have constrained resources and lack a dedicated IT staff that can secure and manage the network and systems. At the same time, homes must tackle the same challenges of securing heterogeneous devices when communicating to the Internet. In this work, we explore combining software-defined networking and proxies with commodity residential Internet routers. We evaluate a "whole home" proxy solution for the Skype video conferencing application to determine the viability of the approach in practice. We find that we are able to automatically detect when a device is about to use Skype and dynamically intercept all of the Skype communication and route it through a proxy while not disturbing unrelated network flows. Our approach works across multiple operating systems, form factors, and versions of Skype. 

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.