ParticipAct
Participact is a large-scale crowdsensing platform that allows the development and deployment of experiments, considering both mobile device and server side. It considers not only technical issues but also human […]
Participact is a large-scale crowdsensing platform that allows the development and deployment of experiments, considering both mobile device and server side. It considers not only technical issues but also human […]
BoT-IoT https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/bot_iot.php N-BaIoT https://archive.ics.uci.edu/ml/datasets/detection_of_IoT_botnet_attacks_N_BaIoT Unified Host and Network Data set https://csr.lanl.gov/data/2017/ IoT Network Intrusion https://ieee-dataport.org/open-access/iot-networkintrusion-dataset UNSW IoT Attack https://iotanalytics.unsw.edu.au/attack-data AMPds http://ampds.org/ UK-DALE https://jack-kelly.com/data/
The Botnet data set was developed by combining the data traces of ISOT HTTP botnet data set, ISCX 2012 IDS data set, and Botnet traffic generated by the malware capture […]
The Botnet data set was developed by combining the data traces of ISOT HTTP botnet data set, ISCX 2012 IDS data set, and Botnet traffic generated by the malware capture […]
A representative data set named ISCX VPN 2016,9 for real world traffic is developed where a set of tasks is defined that exhibit diversity. The data are collected for different […]
A knowledge-based strategy for selecting and managing technologies and artifacts (Big Data, data, information, knowledge, and intelligence) ensure great benefit from IoE’s capacity to provide enhanced intelligent services. This post […]
AMD is a labeled data set that includes comprehensive profile information of malwares [118]. The data set consists of 24 553 samples that are categorized in 135 different types of […]
Kharon data set is developed for studying the Andriod malware behavior under the Kharon project. The Kharon data set consists of malware that are totally reversed and documented. It consists […]
SandDroid3 is an automatic analysis system that performs static and dynamic analysis of the Andriod applications [116]. Static analysis includes basic information extraction, certification analysis, category analysis, permission analysis, […]
The Drebin2 data set is a part of the MobileSandbox project. This data set consists of 5560 malware applications that includes more than 179 malware families. The samples for the […]
Andriod Malware Genome project1 has developed the Andriod malware data set (AMD) with the aim to systematize and categorized existing Andriod malware. The data set consists of 1200 malware samples […]
BiG-IoT focuses on addressing the semantic and organizational levels of IoT interoperability issues by creating the BiG-IoT API. The Web API and semantic information representation models are defined in cooperation […]