| 1. |
- Brötzmann, Leif, et al.
(author)
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Securing Embedded Devices through Obfuscation with Predictable Size and Execution Overhead
- 2023
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In: International Conference on Embedded Wireless Systems and Networks. - 2562-2331.
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Conference paper (peer-reviewed)abstract
- Embedded devices compute and store data locally. Thus, contained sensitive data or code requires extra layers of security. In addition to hardware protection, software obfuscation allows for added code and data protection. Available obfuscation techniques, however, are complex, and their resource costs are difficult to predict, rendering them hard to deploy to resource-constrained devices. This holds especially when multiple techniques are combined. This work introduces obfuscation with predictable size and runtime overhead and tailors software obfuscation to the inherent resource limitations of embedded devices. Accurate predictions of size and execution overhead allow dynamic obfuscation utilizing all of the sparse resources. The implemented framework combines several predictable obfuscation techniques with granular control over their parameters, thus allowing precise control over the resulting resource cost. Our evaluations compare our techniques to state-of-the-art approaches, attesting to the precise prediction of our framework. However, the current implementation is best used on small programs or selected parts, showing at least twice the overhead.
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| 2. |
- Harms, Laura, 1991, et al.
(author)
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Grace: Low-cost time-synchronized GPIO tracing for IoT testbeds
- 2023
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In: Computer Networks. - : Elsevier BV. - 1389-1286. ; 228
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Journal article (peer-reviewed)abstract
- Testbeds have become a vital tool for evaluating and benchmarking applications and algorithms in the Internet of Things (IoT). IoT testbeds commonly consist of low-power IoT devices augmented with observer nodes providing control, debugging, logging, and often also power-profiling capabilities. Today, the research community operates numerous testbeds, sometimes with hundreds of IoT nodes, to allow for detailed and large-scale evaluation. Most testbeds, however, lack opportunities for tracing distributed program execution with high accuracy in time, for example, via minimally invasive, distributed GPIO tracing. And the ones that do, like Flocklab, are built from custom hardware, which is often too complex, inflexible, or expensive to use for other research groups. This paper closes this gap and introduces Grace, a low-cost, retrofittable, distributed, and time-synchronized GPIO tracing system built from off-the-shelf components, costing less than €20 per node. Grace extends observer nodes in a testbed with (1) time-synchronization via wireless sub-GHz transceivers and (2) logic analyzers for GPIO tracing and logging, enabling time-synchronized GPIO tracing at a frequency of up to 8 MHz. We deploy Grace in a testbed and evaluate it, showing that it achieves an average time synchronization error between nodes of 1.53 μs using a single time source, and 15.3 μs between nodes using different time sources, sufficient for most IoT applications.
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| 3. |
- Harms, Laura, 1991, et al.
(author)
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TSCH Meets BLE: Routed Mesh Communication Over BLE
- 2023
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In: Proceedings - 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023. ; , s. 187-195
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Conference paper (peer-reviewed)abstract
- Bluetooth Low Energy (BLE) is the prevalent communication protocol for the Internet of Things. However, for time-critical applications requiring time-synchronized multi-hop networks with often multiple node exchanging data at the same time slot, BLE lacks a solution. Instead, we commonly see IEEE 802.15.4 being used with its Time-Slotted Channel Hopping (TSCH) MAC layer. In this work, we build TBLE, which brings the established TSCH protocol to BLE, enabling BLE to be used for time-synchronized routed mesh communication. We show that in experimental testbed deployments, TBLE achieves similar performance to TSCH, with the possibility for lower average latencies of up to 20%. Moreover, due to the higher spectral efficiency of BLE compared with IEEE 802.15.4 (40 vs. 16 channels), more parallel routed communications are possible with TBLE, further reducing latency and increasing throughput.
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| 4. |
- Hojjat, Ali, et al.
(author)
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ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training
- 2023
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In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. - 2160-7516 .- 2160-7508. ; 2023-June, s. 1130-1139
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Conference paper (peer-reviewed)abstract
- Progressive compression allows images to start loading as low-resolution versions, becoming clearer as more data is received. This increases user experience when, for example, network connections are slow. Today, most approaches for image compression, both classical and learned ones, are designed to be non-progressive. This paper introduces ProgDTD, a training method that transforms learned, non-progressive image compression approaches into progressive ones. The design of ProgDTD is based on the observation that the information stored within the bottleneck of a compression model commonly varies in importance. To create a progressive compression model, ProgDTD modifies the training steps to enforce the model to store the data in the bottleneck sorted by priority. We achieve progressive compression by transmitting the data in order of its sorted index. ProgDTD is designed for CNN-based learned image compression models, does not need additional parameters, and has a customizable range of progressiveness. For evaluation, we apply ProgDTD to the hyperprior model, one of the most common structures in learned image compression. Our experimental results show that ProgDTD performs comparably to its non-progressive counterparts and other state-of-the-art progressive models in terms of MS-SSIM and accuracy.
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| 5. |
- Rathje, Patrick, et al.
(author)
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ALADIn: Autonomous Linear Antenna Delay Inference on Resource-Constrained Ultra-Wideband Devices
- 2023
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In: International Conference on Embedded Wireless Systems and Networks. - 2562-2331.
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Conference paper (peer-reviewed)abstract
- Enabling precise indoor localization in a cheap and small package, Ultra-Wideband (UWB) transceivers bring decimetre-accurate ranging to resource-constrained IoT devices. Due to hardware-induced signal processing delays, device-specific antenna calibration enables the most accurate ranging results. This work introduces ALADIn for estimation and calibration of antenna delays in an autonomous manner, removing the need for manual labor and external hardware or computation. Based on known geometry, our approach allows already deployed devices to utilize their ranging and computational capabilities to optimize delays and reduce ranging errors autonomously. At its heart, ALADIn combines an efficient all-to-all ranging primitive with ordinary least squares inference. We conduct both extensive simulations and on-site evaluations. Our simulation results indicate that the proposed approach performs similarly to available calibration methods while being computationally less expensive. Deployed on three testbeds, we analyze the calibration performance on up to 14 DWM1001 devices. For one, the proposed calibration reduces mean absolute error alongside the standard deviation: from uncali-brated 10.7 (7.0 SD) cm to 6.7 (4.2 SD) cm, which is also lower than the 8.1 (5.7 SD) cm of error induced by factory-calibrated values. In addition, our results highlight the quality of measurements, i.e., pairwise variances, and further exhibit the potential of excluding multipath-affected links from the estimation process. Our implementation builds on Zephyr RTOS and is released as open-source.
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| 6. |
- Rathje, Patrick, et al.
(author)
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STARC: Decentralized Coordination Primitive on Low-Power IoT Devices for Autonomous Intersection Management
- 2023
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In: Journal of Sensor and Actuator Networks. - 2224-2708. ; 12:4
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Journal article (peer-reviewed)abstract
- Wireless communication is an essential element within Intelligent Transportation Systems and motivates new approaches to intersection management, allowing safer and more efficient road usage. With lives at stake, wireless protocols should be readily available and guarantee safe coordination for all involved traffic participants, even in the presence of radio failures. This work introduces STARC, a coordination primitive for safe, decentralized resource coordination. Using STARC, traffic participants can safely coordinate at intersections despite unreliable radio environments and without a central entity or infrastructure. Unlike other methods that require costly and energy-consuming platforms, STARC utilizes affordable and efficient Internet of Things devices that connect cars, bicycles, electric scooters, pedestrians, and cyclists. For communication, STARC utilizes low-power IEEE 802.15.4 radios and Synchronous Transmissions for multi-hop communication. In addition, the protocol provides distributed transaction, election, and handover mechanisms for decentralized, thus cost-efficient, deployments. While STARC’s coordination remains resource-agnostic, this work presents and evaluates STARC in a roadside scenario. Our simulations have shown that using STARC at intersections leads to safer and more efficient vehicle coordination. We found that average waiting times can be reduced by up to 50% compared to using a fixed traffic light schedule in situations with fewer than 1000 vehicles per hour. Additionally, we design platooning on top of STARC, improving scalability and outperforming static traffic lights even at traffic loads exceeding 1000 vehicles per hour.
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