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Nigel Topham

Publications and source records attributed to Nigel Topham.

3 recordsLinked to original sources

Remote-Timer-as-a-Service: Efficient Microarchitectural Leakage in the Cloud with Remote Timers

Edge computing solutions have become a crucial part of the industry, delivering fast, flexible and scalable applications close to the end users, with typical use cases including dynamic content creation, image resizing and chatbots. Cloudflare Workers is one such framework, which handles millions of HTTP requests per second worldwide. To reduce start-up latency, Cloudflare Workers removes process-isolation boundaries between multiple tenants and leverages language-level isolation. This architecture poses the risk of Spectre attacks. To mitigate these, Cloudflare Workers previously introduced several countermeasures such as restricted timer measurements, no shared memory, no multithreading and Dynamic Process Isolation (DyPrIs), detecting potential attacks and process-isolating potentially malicious scripts. We demonstrate that the production implementation of DyPrIs was insufficient. We adopt microarchitectural amplification techniques and discover various possibilities to measure time in the production environment of Cloudflare Workers. Given these techniques, we show that freezing and coarsening timers in the Cloudflare Workers security model is insufficient. Leveraging both timing amplification and remote timers, we demonstrate a remote Spectre attack that leaks a JWT token from a co-located victim worker in the Cloudflare Workers production environment. We outperform the existing attack by orders of magnitude, going from 2 bit/min to up to 12 bit/s at an accuracy of 99.16%, posing an immediate risk to customer data. Following our end-to-end attack, Cloudflare Workers mitigated it in a coordinated effort by integrating the V8 Sandbox limiting transient access to 64-bit pointers, improving the detection capabilities of DyPrIs, and deploying hardware-assisted MPK-based in-process isolation to confine each tenant heap under a dedicated memory-protection key.

cs.CR

Integrating HW/SW Functionality for Flexible Wireless Radio

Current methods of implementing wireless radio typically take one of two forms; either dedicated fixed-function hardware, or pure Software Defined Radio (SDR). Fixed function hardware is efficient, but being specific to each radio standard it lacks flexibility, whereas Software Defined Radio is highly flexible but requires powerful processors to meet real-time performance constraints. This paper presents a hybrid hardware/software approach that aims to combine the flexibility of SDR with the efficiency of dedicated hardware solutions. We evaluate this approach by simulating five variants of the IEEE 802.15.4 protocol, commonly known as Zigbee, and demonstrate the range of performance and power consumption characteristics for different accelerator and software configurations. Across the spectrum of configurations we see power consumption varies from 8% to 38% of a dedicated hardware implementation, and show how the hybrid approach allows a new modulation standard to be retrofitted to an existing design, with only a modest increase in power consumption.

cs.AR

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their high computational requirements mean that use on mass market embedded platforms is challenging. Meanwhile, trends in low-cost, low-power processing are towards massive parallelism and heterogeneity, making it difficult for robotics and vision researchers to implement their algorithms in a performance-portable way. In this paper we introduce SLAMBench, a publicly-available software framework which represents a starting point for quantitative, comparable and validatable experimental research to investigate trade-offs in performance, accuracy and energy consumption of a dense RGB-D SLAM system. SLAMBench provides a KinectFusion implementation in C++, OpenMP, OpenCL and CUDA, and harnesses the ICL-NUIM dataset of synthetic RGB-D sequences with trajectory and scene ground truth for reliable accuracy comparison of different implementation and algorithms. We present an analysis and breakdown of the constituent algorithmic elements of KinectFusion, and experimentally investigate their execution time on a variety of multicore and GPUaccelerated platforms. For a popular embedded platform, we also present an analysis of energy efficiency for different configuration alternatives.

cs.RO