IoT
The following data set is modelled after the implementers’ test data in 3GPP TS 33.501 “Security architecture and procedures for 5G System” with the same terminology. The data set corresponds to SUCI (Subscription Concealed Identifier) computation in the 5G UE (User Equipment) for IMSI (International Mobile Subscriber Identity) based SUPI (Subscription Permanent Identifier) and ECIES Profile A.
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Vibration measurement on SAG mill drive motor for Energy harvesting or predictive maintenance
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Presented here is a dataset used for our SCADA cybersecurity research. The dataset was built using our SCADA system testbed described in our paper below [*]. The purpose of our testbed was to emulate real-world industrial systems closely. It allowed us to carry out realistic cyber-attacks.
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Message Queuing Telemetry Transport (MQTT) protocol is one of the most used standards used in Internet of Things (IoT) machine to machine communication. The increase in the number of available IoT devices and used protocols reinforce the need for new and robust Intrusion Detection Systems (IDS). However, building IoT IDS requires the availability of datasets to process, train and evaluate these models. The dataset presented in this paper is the first to simulate an MQTT-based network. The dataset is generated using a simulated MQTT network architecture.
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The demo data set consists the propagation path distances of AT & T North America Netowork Topology. The geographical node positions (latitude and longitude) along with the adjacency matrix has been found out from International Topology Zoo and the data set has been formed using the available data. This set has been used in Joint localization prolem of Controller and Hypervisor instances in vSDN enebled 5G Network.
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Underground UE statistics measurements captured on u-blox SARAN211 NB-IoT device, frequency band 20. Signal waveform captured by means of Rohde&Schwartz TSMW device. The samples were taken along ca. 1600m of level -2 underground tunnel system under Lyngby Campus of Technical University of Denmark.
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Dataset used for "A Machine Learning Approach for Wi-Fi RTT Ranging" paper (ION ITM 2019). The dataset includes almost 30,000 Wi-Fi RTT (FTM) raw channel measurements from real-life client and access points, from an office environment. This data can be used for Time of Arrival (ToA), ranging, positioning, navigation and other types of research in Wi-Fi indoor location. The zip file includes a README file, a CSV file with the dataset and several Matlab functions to help the user plot the data and demonstrate how to estimate the range.
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