3 research outputs found

    Passive classification of Wi-Fi enabled devices

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    We propose a method for classifying Wi-Fi enabled mobile handheld devices (smartphones) and non-handheld devices (laptops) in a completely passive way, that is resorting neither to traffic probes on network edge devices nor to deep packet inspection techniques to read application layer information. Instead, classification is performed starting from probe requests Wi-Fi frames, which can be sniffed with inexpensive commercial hardware. We extract distinctive features from probe request frames (how many probe requests are transmitted by each device, how frequently, etc.) and take a machine learning approach, training four different classifiers to recognize the two types of devices. We compare the performance of the different classifiers and identify a solution based on a Random Decision Forest that correctly classify devices 95% of the times. The classification method is then used as a pre-processing stage to analyze network traffic traces from the wireless network of a university building, with interesting considerations on the way different types of devices uses the network (amount of data exchanged, duration of connections, etc.). The proposed methodology finds application in many scenarios related to Wi-Fi network management/optimization and Wi-Fi based services

    A hybrid BLE and Wi-Fi localization system for the creation of study groups in smart libraries

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    Campus libraries in modern universities provide students with group study areas where they can work and study collaboratively. In this paper, we propose a complete solution for the creation of study groups in future smart libraries featuring (i) a smartphone application to create study groups, (ii) a hybrid Bluetooth Low Energy (BLE) and Wi-Fi indoor positioning system to localize study groups and (iii) a server-based infrastructure based on MQTT and Node-RED to advertise study groups to other students. We describe in details all components of the architecture and perform an experimental evaluation of the indoor positioning system in a realistic scenario
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