Uwe Muller, Eicke Hauck, Timm Welz, Jiska Classen, Matthias Hollick (Secure Mobile Networking Lab, TU Darmstadt)

Even though PowerPC mostly disappeared from the consumer device market, its architectural properties continue being popular for highly specialized systems. This particularly includes embedded systems with real-time requirements that are deeply integrated into critical infrastructures as well as aeronautics, transportation, control systems in power plants, etc. One example is Terrestrial Trunked Radio (TETRA), a digital radio system used in the public safety domain and deployed in more than 120 countries worldwide: base stations of at least one of the main vendors are based on PowerPC. Despite the criticality of the aforementioned systems, many follow a security by obscurity approach and there are no openly available analysis tools. While analyzing a TETRA base station, we design and develop a set of analysis tools centered around a PowerPC binary patcher. We further create various dynamic tooling on top, including a fast memory dumper, function tracer, flexible patching capabilities at runtime, and a fuzzer. We describe the genesis of these tools and detail the binary patcher, which is general in nature and not limited to our base station under test.

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Target-Centric Firmware Rehosting with Penguin

Andrew Fasano, Zachary Estrada, Luke Craig, Ben Levy, Jordan McLeod, Jacques Becker, Elysia Witham, Cole DiLorenzo, Caden Kline, Ali Bobi (MIT Lincoln Laboratory), Dinko Dermendzhiev (Georgia Institute of Technology), Tim Leek (MIT Lincoln Laboratory), William Robertson (Northeastern University)

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OblivSketch: Oblivious Network Measurement as a Cloud Service

Shangqi Lai (Monash University), Xingliang Yuan (Monash University), Joseph K. Liu (Monash University), Xun Yi (RMIT University), Qi Li (Tsinghua University), Dongxi Liu (Data61, CSIRO), Surya Nepal (Data61, CSIRO)

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Taking a Closer Look at the Alexa Skill Ecosystem

Christopher Lentzsch (Ruhr-Universität Bochum), Anupam Das (North Carolina State University)

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Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang (Tsinghua University), Jiaming Mu (Tsinghua University), Neil Zhenqiang Gong (Duke University), Qi Li (Tsinghua University), Bin Liu (West Virginia University), Mingwei Xu (Tsinghua University)

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