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56 results for “internet of things”
Results for scheme by Schürmann and Sigg from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the results from the evaluation of the paper by Schürmann and Sigg in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p>
Processed data from Mobile scenario from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the processed data from the Mobile scenario in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p>
Results for scheme by Truong et al. from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the results from the evaluation of the paper by Truong et al. in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p>
Results for scheme by Shrestha et al. from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the results from the evaluation of the paper by Shrestha et al. in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p>
Results for scheme by Miettinen et al. from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the results from the evaluation of the paper by Miettinen et al. in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p>
Results for scheme by Karapanos et al. from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the results from the evaluation of the paper by Karapanos et al. in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p>
PEMANFAATAN BIG DATA ANALYTIC BERBASIS INTERNET OF THINGS SEBAGAI SUMBER DATA DALAM PENGENDALIAN COVID-19
<p>Tingginya angka kasus dan angka kematian pasien terkonfirmasi positif COVID-19 masih merupakan masalah besar di dunia dan di Indonesia. Banyaknya tenaga medis yang terpapar bahkan meninggal akibat COVID-19 juga belum dapat teratasi. Oleh sebab itu para peneliti mengembangkan berbagai usaha pencegahan dan penanggulangan, termasuk memanfaatkan analisis Big Data. Tujuan review ini adalah untuk menjelaskan bagaimana potensi analisis Big Data berbasis Internet of Things (IoT) dalam pencegahan dan penanggulangan COVID-19. Metode yang digunakan adalah mengkaji literatur yang bersumber dari database Pubmed, Sciencedirect, dan Proquest. Penelusuran literatur menggunakan beberapa kata kunci yang terkait topik. Dari literatur yang membahas macam-macam teknologi IoT, dapat disimpulkan bahwa teknologi IoT seperti perangkat wearable, drone, robot, dan aplikasi smartphone sangat direkomendasikan penggunaannya dalam penanggulangan COVID-19. Namun tentu saja sebelum digunakan di masyarakat luas, perlu dipertimbangkan beberapa hal seperti sumber daya manusia, finansial, dan keamanan serta privasi data.</p>
Clinical Study of Three Plus Two Type Early Diagnosis of Pulmonary Nodules in Medical Internet of Things
ClinicalTrials.gov study NCT02773992. IPD Sharing: NO. Countries: 1. Publications: 0.
Advanced Patient Monitoring and A.I. Supported Outcomes Assessment in Lung Cancer Using Internet of Things Technologies (A.I. - APALITT)
ClinicalTrials.gov study NCT05815472. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Randomized Controlled Study on the Improvement of Medical Experience for Patients With Radiation-induced Oropharyngeal Mucositis Based on the RIS System of the Internet of Things
ClinicalTrials.gov study NCT07126457. IPD Sharing: NO. Countries: 1. Publications: 0.
Code for the lecture notes: "Green Computing for the Internet of Things"
<p>This dataset contains the supplementary files for the lecture and practical "Green Computing for the Internet of Things" that was given at the SusTrainable Summer School 2022, Rijeka, Croatia, July 4–5, 2022.</p> <p>This work acknowledges the support of the ERASMUS+ project “SusTrainable—Promoting<br> Sustainability as a Fundamental Driver in Software Development Training and Education”, no.<br> 2020–1–PT01–KA203–078646.</p> <p>https://sustrainable.uniri.hr/</p> <p>It was originally uploaded at: https://ftp.cs.ru.nl/Clean/mTask/SUSTRAINABLE2022/</p> <p>The dataset contains the following files:</p> <ul> <li>slides.pdf: the slides for the the lecture.</li> <li>exercises.zip: the installation instructions and assignments.</li> <li>exercises.pdf: the reader for the exercises done during the practical.</li> <li>exercises-oob.zip: a copy of exercises.zip but this includes all packages, dependencies, and binaries for the build system nitrile.</li> </ul>
UDP Flood Attack Pattern on Internet of Things Network Dataset
<p><strong>Investigating UDP Flood Attack Pattern on Internet of Things Network</strong></p> <p><em>status: on review</em></p> <p>Abstract: UDP does not have mechanism for retransmission when a transmitting error happens, it makes this protocol to be used as a DDoS attack tool against Internet of Things (IoTs) networks. This research work attempts to analyze the UDP Flood attacks packets dataset captured from an Io|T testbed network by Wireshark.</p> <p>A feature extraction process on generated CSV file was performed and then the feature extraction result are examined to find patterns of UDP flood attack packet. Lastly, the patterns are visualized to provide easy pattern recognition.</p>
Constrained Application Protocol (CoAP) Internet of Things Protocol Dataset
<p><strong>Implementation of Constrained Application Protocol on IoT using Constrained RESTful Environments Constrained Device.</strong><br> <em>status : on repository</em></p> <p>This study discusses the implementation of the Constrained Application Protocol (CoAP) using Constrained RESTful Environments (CoRE) on RFC 7252 which is used as a research parameter.</p> <p>The implementation of this Limited Application Protocol uses Internet of Things (IoT) technology. The testing technique is carried out offline and the device used is based on the constrained device. Network performance testing parameters in this study are UDP throughput, UDP delay, UDP packet loss and UDP packet delivery ratio. Testing network performance with LED and Buzzer output produces the largest average UDP throughput, namely 4.5737 Kbps while the smallest average throughput is 1.2293 Kbps, the largest average UDP delay result is 2 seconds and the smallest average is 0.6 seconds, then the average UDP packet loss yield is 0% while the average successful packet delivery ratio is 100%. From the results of this test, the Constrained Application Protocol (CoAP) has smaller network performance results than the HyperText Transfer Protocol (HTTP) to be implemented in Internet of Things (IoT) technology.</p>
Message Queue Telemetry Transport (MQTT) Protocol on Internet of Thing Dataset
<p><strong>Performance Analysis of Message Queue Telemetry Transport (MQTT) Protocol on Internet of Thing (IoT) </strong><br> <em>status : on review</em></p> <p>Internet of Things (IoT) is a system where devices are connected and allows information exchange among them. It also allows devices/objects to interact directly with other objects or commonly refers to Machine-to-Machine (M2M) communication. Message Queue Telemetry Transport (MQTT) is machine-to-machine connectivity protocol, which is designed as messages delivery service that gives different level of Quality of Service (QoS) i.e.: level 0, 1 and 2 for variety of use cases, provides architecture of publish/subscribe and supports multicasting message. The importance feature of MQTT is low overhead for efficient communication between devices.</p> <p>This work implements MQTT using Mosquito Broker, which has a function to regulate the delivery of messages between Publisher and Subscriber using poll system call to handle multiple network socket in one thread. With a scenario of increasing number of nodes at each experiment, MQTT Protocol has an average overall delay of 0.0029 seconds, an average throughput of 218 Kbps, average of packet loss of 0.2% and average of packet delivery ratio of 99.7%. Of experiment results obtained, the MQTT Protocol has potential to be able to meet the needs of the use of a limited bandwidth network, which can be adjusted with the level of service provided by the MQTT and low packet loss rate.</p>
Ping Flood Attack Pattern Recognition on Internet of Things Network Dataset
<p><strong>Ping Flood Attack Pattern Recognition using K-Means Algorithm in Internet of Things (IoT) Network</strong> <br> <em>status: on repository</em></p> <p>Abstract — This work investigates ping flood attack pattern recognition on Internet of Things (IoT) network. Experiments are conducted on WiFi communication with three different scenarios: normal traffic, attack traffic, and normal-attack combination traffic to create normal dataset, attack dataset, and normal attack (combined) dataset. The datasets are grouped into two clusters i.e.: (i) normal cluster and (ii) attack cluster. Clustering results using implemented K-Means algorithm show the average number of packets on the cluster of attack in total is 95,931 packets, and the average packets on normal cluster in total is 4,068 packets.</p> <p>Accuracy level of the clustering results then is calculated using confusion matrix equation. Based on the confusion matrix calculation, accuracy of clustering using implemented K-Means algorithm was 99.94%. The true negative rate reaches up to 98.62%, true positive rate is 100%, the false negative rate is 0%, and the false positive rate reaches 1.38%.</p>
Audio data from Mobile scenario from "Perils of Zero-Interaction Security in the Internet of Things"
<p>This deposit contains the recorded audio data from the Mobile scenario in the paper "Perils of Zero Interaction Security in the Internet of Things" by Mikhail Fomichev, Max Maass, Lars Almon, Alejandro Molina, Matthias Hollick, in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, Issue 1. See the <a href="https://dx.doi.org/10.5281/zenodo.2537721">index of all related datasets</a> for more details on the paper, and see the included README for details on this dataset.</p> <p>This dataset also has a second part that contains the sensor data data recorded in this scenario, which is not access controlled. See <a href="http://dx.doi.org/10.5281/zenodo.2537703">this deposit</a> for more details.</p>
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