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Atomic force microscopy (AFM) provides the opportunity to perform fundamental and mechanistic observations of complex, dynamic, and transient systems and ultimately link material microstructure and its evolution during tribological interactions. This investigation focuses on the evolution of a dynamic fluoropolymer tribofilm formed during sliding of polytetrafluoroethylene (PTFE) mixed with 5 wt% alpha-phase alumina particles against 304L stainless steel. Sliding was periodically interrupted for AFM topography scans. The average film roughness, the average friction coefficient, and polymer wear rate based on sample height recession were recorded as a function of increasing sliding cycles. Topographical maps suggested tribofilm nucleates in grooves of the steel countersample, spreads, and develops into a uniform film through sliding. Prominent nanoscale features were visible around 10,000 sliding cycles and thereafter. Scanning electron microscopy and energy-dispersive X-ray spectroscopy showed good correlations between these features and aluminum-rich domains, suggesting the presence of alumina particles on the surface.

 

The security of residential networks can vary greatly. These networks are often administrated by end-users who may lack security expertise or the resources to adequately defend their networks. Insecure residential networks provide attackers with opportunities to infiltrate systems and create a platform for launching powerful attacks. To address these issues, we introduce a new approach that uses software-defined networking (SDN) to allow home users to outsource their security maintenance to a cloud-based service provider. Using this architecture, we show how a novel network-based two-factor authentication approach can be used to protect Internet of Things devices. Our approach works without requiring modifications to end-devices. We further show how security modules can enforce protocol messages to limit the attack surface in vulnerable devices. Our analysis shows that the system is effective and adds less than 50 milliseconds of delay to the start of a connection with less than 100 microseconds of delay for subsequent packets. 

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. 

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. 

Three-dimensional (3D) printing has expanded beyond the mere patterned deposition of melted solids, moving into areas requiring spatially structured soft matter—typically materials composed of polymers, colloids, surfactants, or living cells. The tunable and dynamically variable rheological properties of soft matter enable the high-resolution manufacture of soft structures. These rheological properties are leveraged in 3D printing techniques that employ sacrificial inks and sacrificial support materials, which go through reversible solid–fluid transitions under modest forces or other small perturbations. Thus, a sacrificial material can be used to shape a second material into a complex 3D structure, and then discarded. Here, we review the sacrificial materials and related methods used to print soft structures. We analyze data from the literature to establish manufacturing principles of soft matter printing, and we explore printing performance within the context of instabilities controlled by the rheology of soft matter materials. 

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.