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- Kanwar, John, et al.
(författare)
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JamSense : Interference and Jamming Classification for Low-power Wireless Networks
- 2021
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Ingår i: Proceedings of the 2021 13Th IFIP Wireless and Mobile Networking Conference (WMNC). - : IEEE. - 9783903176423 ; , s. 9-16
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Konferensbidrag (refereegranskat)abstract
- Low-power wireless networks transmit at low output power and are hence susceptible to cross-technology interference. The latter may cause packet loss which may waste scarce energy resources by requiring the retransmission of packets. Jamming attacks are even more harmful than cross-technology interference in that they may totally prevent packet reception and hence disturb or even disrupt applications. Therefore, it is important to recognize such jamming attacks. In this paper, we present JamSense. JamSense extends SpeckSense, a system that is able to detect multiple sources of interference, with the ability to classify jamming attacks. As SpeckSense, JamSense runs on resource-constrained nodes. Our experimental evaluation on real hardware shows that JamSense is able to identify jamming attacks with high accuracy while not classifying Bluetooth or WiFi interference as jamming attacks.
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- Löscher, Andreas, et al.
(författare)
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Efficient and Flexible Sensornet Checkpointing
- 2014
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Ingår i: Wireless Sensor Networks, volume 8354. - Cham : Springer International Publishing. - 9783319046501 - 9783319046518 ; , s. -65
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Konferensbidrag (refereegranskat)abstract
- Developing sensornet software is difficult partly because ofthe limited visibility of the system state of deployed nodes. Sensor-net checkpointing is a method that allows developers to save and restore full system state of nodes. We present four extensions to sensornetcheckpointing—compression, binary diffs, selective checkpointing, and checkpoint inspection—that reduce the time required for checkpointing operations considerably, and improve the granularity at which system state can be examined and manipulated down to the variable level. We show through an experimental evaluation that the checkpoint sizes can be reduced by 70%-93%, and the time can be reduced by at least 50% because of these improvements. The reduced time and increased granularity benefits multiple checkpointing use cases, including automated testing, network visualization, and software debugging.
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- Martina, Brachmann, et al.
(författare)
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IEEE 802.15. 4 TSCH in Sub-GHz : Design Considerations and Multi-band Support
- 2019
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Ingår i: Proceedings of the IEEE LCN. - : IEEE COMPUTER SOC. - 9781728110288 ; , s. 42-50
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Konferensbidrag (refereegranskat)abstract
- In this paper, we address the support of Time-Slotted Channel Hopping (TSCH) on multiple frequency bandswithin a single TSCH network. This allows to simultaneously runapplications with different requirements on link characteristicsand to increase resilience against interference. To this end, wefirst enable sub-GHz communication in TSCH, which has beenprimarily defined for the 2.4 GHz band. Thereafter, we proposetwo designs to support multiple physical layers in TSCH on thesame nodes. Our experimental evaluation shows that TSCH isapplicable in a wide range of data rates between 1.2 kbps and1000 kbps. We find that data rates of 50 kbps and below have along communication range and a nearly perfect link symmetry,but also have a 20x higher channel utilization compared to higherdata rates, increasing the risk of collisions. Using these findings,we show the advantages of the multi-band support on the exampleof synchronization accuracy when exchanging TSCH beaconswith a low data rate and application data at a high data rate.
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- Oikonomou, George, et al.
(författare)
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The Contiki-NG open source operating system for next generation IoT devices
- 2022
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Ingår i: SoftwareX. - : Elsevier B.V.. - 2352-7110. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Contiki-NG (Next Generation) is an open source, cross-platform operating system for severely constrained wireless embedded devices. It focuses on dependable (reliable and secure) low-power communications and standardised protocols, such as 6LoWPAN, IPv6, 6TiSCH, RPL, and CoAP. Its primary aims are to (i) facilitate rapid prototyping and evaluation of Internet of Things research ideas, (ii) reduce time-to-market for Internet of Things applications, and (iii) provide an easy-to-use platform for teaching embedded systems-related courses in higher education. Contiki-NG started as a fork of the Contiki OS and retains many of its original features. In this paper, we discuss the motivation behind the creation of Contiki-NG, present the most recent version (v4.7), and highlight the impact of Contiki-NG through specific examples. © 2022 The Authors
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- Perez-Ramirez, Daniel F., et al.
(författare)
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DeepGANTT: A Scalable Deep Learning Scheduler for Backscatter Networks
- 2023
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Ingår i: IPSN '23: Proceedings of the 22nd International Conference on Information Processing in Sensor Networks. - New York, NY, United States : Association for Computing Machinery (ACM). - 9798400701184 ; , s. 163-
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Konferensbidrag (refereegranskat)abstract
- Novel backscatter communication techniques enable battery-free sensor tags to interoperate with unmodified standard IoT devices, extending a sensor network’s capabilities in a scalable manner. Without requiring additional dedicated infrastructure, the battery-free tags harvest energy from the environment, while the IoT devices provide them with the unmodulated carrier they need to communicate. A schedule coordinates the provision of carriers for the communications of battery-free devices with IoT nodes. Optimal carrier scheduling is an NP-hard problem that limits the scalability of network deployments. Thus, existing solutions waste energy and other valuable resources by scheduling the carriers suboptimally. We present DeepGANTT, a deep learning scheduler that leverages graph neural networks to efficiently provide near-optimal carrier scheduling. We train our scheduler with optimal schedules of relatively small networks obtained from a constraint optimization solver, achieving a performance within 3% of the optimum. Without the need to retrain, our scheduler generalizes to networks 6 × larger in the number of nodes and 10 × larger in the number of tags than those used for training. DeepGANTT breaks the scalability limitations of the optimal scheduler and reduces carrier utilization by up to compared to the state-of-the-art heuristic. As a consequence, our scheduler efficiently reduces energy and spectrum utilization in backscatter networks.
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- Poncelet, Clément, et al.
(författare)
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So Many Fuzzers, So Little Time : Experience from Evaluating Fuzzers on the Contiki-NG Network (Hay)Stack
- 2022
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Ingår i: iWOAR 2022. - New York, NY, USA : ACM.
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Konferensbidrag (refereegranskat)abstract
- Fuzz testing (“fuzzing”) is a widely-used and effective dynamic technique to discover crashes and security vulnerabilities in software, supported by numerous tools, which keep improving in terms of their detection capabilities and speed of execution. In this paper, we report our findings from using state-of-the-art mutation-based and hybrid fuzzers (AFL, Angora, Honggfuzz, Intriguer, MOpt-AFL, QSym, and SymCC) on a non-trivial code base, that of Contiki-NG, to expose and fix serious vulnerabilities in various layers of its network stack, during a period of more than three years. As a by-product, we provide a Git-based platform which allowed us to create and apply a new, quite challenging, open-source bug suite for evaluating fuzzers on real-world software vulnerabilities. Using this bug suite, we present an impartial and extensive evaluation of the effectiveness of these fuzzers, and measure the impact that sanitizers have on it. Finally, we offer our experiences and opinions on how fuzzing tools should be used and evaluated in the future.
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