The Internet of Things is expanding and since IoT devices and IoT networks are used in many crucial areas in modern societies, ranging from security and military applications to healthcare monitoring and production efficiency, the need to secure these devices is of great importance. Intrusion detection systems (IDS) play a significant role in securing IoT networks as their goal is to detect intruders that have gained access to one or several IoT nodes. While most IDS have been designed to detect a specific or at most a few attacks, the DETONAR framework detects multiple attacks. However, it is run on a designated sniffer network which adds additional cost in terms of hardware and maintenance. In this paper, we propose DETONAR-Light, adapting DETONAR to run using data collected at a border router rather than on sniffer logs. Our experiments show that this is possible almost without any decrease of detection and attack classification rate for many attacks.

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Wireless low-power transceivers used in sensor networks typically operate in unlicensed frequency bands that are subject to external radio interference caused by devices transmitting at much higher power.communication protocols should therefore be designed to be robust against such interference. A critical building block of many protocols at all layers is agreement on a piece of information among a set of nodes. At the MAC layer, nodes may need to agree on a new time slot or frequency channel, at the application layer nodes may need to agree on handing over a leader role from one node to another. Message loss caused by interference may break agreement in two different ways: none of the nodes uses the new information (time slot, channel, leader) and sticks with the previous assignment, or-even worse-some nodes use the new information and some do not. This may lead to reduced performance or failures. In this paper, we investigate the problem of agreement under external radio interference and point out the limitations of traditional message-based approaches. We propose JAG, a novel protocol that uses jamming instead of message transmissions to make sure that two neighbouring nodes agree, and show that it outperforms message-based approaches in terms of agreement probability, energy consumption, and time-to-completion. We further show that JAG can be used to obtain performance guarantees and meet the requirements of applications with real-time constraints.

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Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols.

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Link quality estimation is a thorny problem in wireless sensor networks, because its accuracy affects the design and the efficiency of networking protocols and applications. Especially in the context of low-power wireless, estimating the link quality poses a sort of catch-22 dilemma, whereby a large number of packet samples are required to accurately estimate a channel, but only a few samples should be used due to limited energy resources. This paradox becomes even more severe in mobile wireless sensor networks, since the high variability of the medium imposes even stricter constraints on the timing in which the estimation has to be carried out. In this paper we propose the Triangle Metric, a metric that combines geometrically the information of PRR, LQI, and SNR into a robust estimator that guarantees a fast and reliable assessment of the link quality. Our evaluation shows that the triangle metric can identify the quality of links using as few as 10 packet samples, making it an eligible solution for highly mobile sensor networks.@en

Radio interference plays a central role for the performance of Wireless Sensor Networks (WSN). Interference not only leads to packet loss, but it also affects the function of MAC and routing protocols. Hitherto, testing the impact of interference on WSN experimentally has been difficult because of the unavailability of low-cost tools to create reproducible and well-controlled interference patterns. In this demo we present a simple and inexpensive method to generate controllable and repeatable interference patterns for 802.15.4 devices. The demo is presented as a game, where a user is required to achieve a given interference level.

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We address the problem of generating customized, controlled interference for experimental and testing purposes in Wireless Sensor Networks. The known coexistence problems between electronic devices sharing the same ISM radio band drive the design of new solutions to mitigate interference. The validation of these techniques and the assessment of protocols under external interference require the creation of reproducible and well-controlled interference patterns on real nodes, a nontrivial and time-consuming task. In this paper, we study methods to generate a precisely adjustable level of interference on a specific channel, with lowcost equipment and rapid calibration. We focus our work on the platforms carrying the CC2420 radio chip. We show that, by setting the CC2420 in special mode, we can easily generate repeatable and precise patterns of interference. We show how this method is extremely useful for researchers to quickly investigate the behaviour of sensor network protocols and applications under different patterns of interference. We further evaluate the performance of our proposed method.

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