Sensor networks are made up of small battery-powered sensing devices with wireless communication capabilities, enabling the network to monitor the environment in which it is deployed. Through their flexible and cable-free design these networks open up for new deployment scenarios that were previously not plausible such as during a natural disaster. Motivated by scenarios where centralized oversight is not possible the focus of this thesis is to equip nodes with further adaptability to changes in the links it has with other nodes. This is achieved through contributions in three areas focusing on observations from a node-link perspective. First, the impact the local environment has on the nodes is explored by deploying a sensor network outdoors next to a meteorological station to correlate the variations in link quality to the changes in the environment. The work identifies temperature as the main factor, where through further investigations in a controlled setting, a linear relationship between the decrease in signal quality and the increase in temperature is described. Secondly, the thesis address how nodes in a sensor network can be motivated to exchange data by modeling it as a game. The game theoretic design is motivated by the absence of any centralized control and focus on the nodes as individual users in the network. The presented design motivates the selfish nodes to participate in the exchange of sensor data, showing that it is the best strategy. Lastly, by exploring and understanding how connections in a mobile sensor network occur, nodes are given more flexibility to determine how to send and sample sensor data. This adaptability to contact occurrences is shown to provide better ways of sending data by selecting higher quality links as well as making sampling more energy preserving by reducing the rate in the vicinity of other nodes. / CNDS / WISENET

Sensor networks consist of small sensing devices that collaboratively fulfill a sensing task, such as monitoring the soil in an agricultural field or measuring vital signs in a marathon runner. To avoid cumbersome and expensive cabling, nodes in a sensor network are powered by batteries and communicate wirelessly. As a consequence of the latter, a sensor network's communication is affected by its radio environment, i.e., the environment's propagation characteristics and the presence of other radio devices. This thesis addresses three issues related to the impact of the radio environment on sensor networks. Firstly, in order to draw conclusions from experimental results, it is necessary to assess how the environment and the experiment infrastructure affect the results. We design a sensor network testbed, dubbed Sensei-UU, to be easily relocatable. By performing an experiment in different environments, a researcher can asses the environments’ impact on results. We further augment Sensei-UU with support for mobile nodes. The implemented mobility approach adds only little variance to results, and therefore enables repeatable experiments with mobility. The repeatability of experiments increases the confidence in conclusions drawn from them. Secondly, sensor networks may experience poor communication performance due to cross-technology radio interference, especially in office and residential environments. We consider the problem of detecting and classifying the type of interference a sensor network is exposed to. We find that different sources of interference each leave a characteristic "fingerprint" on individual, corrupt 802.15.4 packets. We design and implement the SoNIC system that enables sensor nodes to classify interference using these fingerprints. SoNIC supports accurate classification in both a controlled and an uncontrolled environment. Finally, we consider transmission errors in an outdoor sensor network. In such an environment, errors occur despite the absence of interference if the signal-to-noise ratio at a receiver is too low. We study the characteristics of corrupt packets collected from an outdoor sensor network deployment. We find that content transformation in corrupt packets follows a specific pattern, and that most corrupt packets contain only few errors. We propose that the pattern may be useful for applications that can operate on inexact data, because it reduces the uncertainty associated with a corrupt packet. / WISENET

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This thesis is focused on network behavior analysis (NBA) designed to detect network attacks. The goal of the thesis is to increase detection accuracy of obfuscated network attacks. Methods and techniques used to detect network attacks and network traffic classification were presented first. Intrusion detection systems (IDS) in terms of their functionality and possible attacks on them are described next. This work also describes principles of selected attacks against IDS. Further, obfuscation methods which can be used to overcome NBA are suggested. The tool for automatic exploitation, attack obfuscation and collection of this network communication was designed and implemented. This tool was used for execution of network attacks. A dataset for experiments was obtained from collected network communications. Finally, achieved results emphasized requirement of training NBA models by obfuscated malicious network traffic.