Glider: A GPU Library Driver for Improved System Security

Legacy device drivers implement both device resource management and isolation. This results in a large code base with a wide high-level interface making the driver vulnerable to security attacks. This is particularly problematic for increasingly popular accelerators like GPUs that have large, complex drivers. We solve this problem with library drivers, a new driver architecture. A library driver implements resource management as an untrusted library in the application process address space, and implements isolation as a kernel module that is smaller and has a narrower lower-level interface (i.e., closer to hardware) than a legacy driver. We articulate a set of device and platform hardware properties that are required to retrofit a legacy driver into a library driver. To demonstrate the feasibility and superiority of library drivers, we present Glider, a library driver implementation for two GPUs of popular brands, Radeon and Intel. Glider reduces the TCB size and attack surface by about 35% and 84% respectively for a Radeon HD 6450 GPU and by about 38% and 90% respectively for an Intel Ivy Bridge GPU. Moreover, it incurs no performance cost. Indeed, Glider outperforms a legacy driver for applications requiring intensive interactions with the device driver, such as applications using the OpenGL immediate mode API

Directional Antenna Diversity for Mobile Devices: Characterizations and Solutions

We report a first-of-its-kind realization of directional transmission for smartphone-like mobile devices using multiple passive directional antennas, supported by only one RF chain. The key is a multi-antenna system (MiDAS) and its antenna selection methods that judiciously select the right antenna for transmission. It is grounded by two measurementdriven studies regarding 1) how smartphones rotate during wireless usage in the field and 2) how orientation and rotation impact the performance of directional antennas under various propagation environments. We implement MiDAS using the WARP platform, and evaluate it usmg a computerized motor to rotate the prototype according to traces collected from smartphone users in the field. Our evaluation shows MiDAS achieves median of 3dB increase in link gain. Combined with rate adaptation and power control, MiDAS also improves goodput and power saving. MiDAS does not require any changes to the network infrastructure, and is therefore suitable for immediate deployment

Eliminating State Entanglement with Checkpoint-based Virtualization of Mobile OS Services

Abstract Mobile operating systems have adopted a service model in which applications access system functionality by interacting with various OS Services in separate processes. These interactions cause application-specific states to be spread across many service processes, a problem we identify as state entanglement. State entanglement presents significant challenges to a wide variety of computing goals: fault isolation, fault tolerance, application migration, live update, and application speculation. We propose CORSA, a novel virtualization solution that uses a lightweight checkpoint/restore mechanism to virtualize OS Services on a per-application basis. This cleanly encapsulates a single application's service-side states into a private virtual service instance, eliminating state entanglement and enabling the above goals. We present empirical evidence that our ongoing implementation of CORSA on Android is feasible with low overhead, even in the worst case of high frequency service interactions

Empowering Cyber-Physical Systems with FADEX.

The proliferation of smart devices in close proximity to end users has massively increased availability of data about our surroundings and hence stimulated a plethora of new services. However, it has also increased the chances of leaking sensitive and private information about end users (e.g., geolocation data, biometric signatures). Loss of trust towards a Cloud provider can lead to a user boycott and requests for deletion of the their remotely stored personal information. While many Cloud services can handle this relatively easily, it is far more cumbersome for many smart services. In fact, the current market of smart services is composed of black-box systems dependent on tight coupling between deployed hardware and the Cloud hosted software stack leaving virtually no freedom to change service provider without considerable redeployment costs

What-If Analysis of Page Load Time in Web Browsers Using Causal Profiling

Web browsers have become one of the most commonly used applications for desktop and mobile users. Despite recent advances in network speeds and several techniques to speed up web page loading such as speculative loading, smart caching, and multi-threading, browsers still suffer from relatively long page load time (PLT). As web applications are receiving widespread attention owing to their cross-platform support and comparatively straightforward development process, they need to have higher performance to compete with native applications. Recent studies have investigated the bottleneck of the modern web browser's performance and conclude that network connection is not the browser's bottleneck anymore. Even though there is still no consensus on this claim, no subsequent analysis has been conducted to inspect which parts of the browser's computation contribute to the performance overhead. In this paper, we apply comprehensive and quantitative what-if analysis on the web browser's page loading process. Unlike conventional profiling methods, we applycausal profiling to precisely determine the impact of each computation stage such as HTML parsing and Layout on PLT. For this purpose, we develop COZ+, a high-performance causal profiler capable of analyzing large software systems such as the Chromium browser. COZ+ highlights the most influential spots for further optimization, which can be leveraged by browser developers and/or website designers. For instance, COZ+ shows that optimizing JavaScript by 40% is expected to improve the Chromium desktop browser's page loading performance by more than 8.5% under typical network conditions