ArticleData in brief2024
Dataset of DDoS attacks on Fibaro home center 3 for smart home security.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DDoS attacks pose a significant security risk to smart homes and can disrupt the functionality and availability of connected devices in the home. This dataset documents Distributed Denial of Service (DDoS) attacks against the Fibaro Home Center 3 central control unit, which is used to automate smart homes within the Internet of Things. The focus is on three types of DDoS attacks: TCP SYN flood, ICMP flood and HTTP flood. Data collection was performed on the local network, where SYN flood and ICMP flood attacks were performed using the hping3 tool, and HTTP flood attack was performed using the LOIC tool. The data was captured using Wireshark software and is available in PCAP and CSV formats, allowing detailed analysis of the network traffic. The logs include information such as timestamps, source and destination IP addresses, protocols, packet lengths, and port numbers. The dataset includes raw and anonymized data for each type of attack. The dataset is a resource for researchers focused on cybersecurity and IoT device protection. It allows simulation and analysis of DDoS attacks on a specific IoT device, providing insight into attack patterns and the effectiveness of defenses. The simplicity and specialization of the dataset makes it a practical resource for developing and testing intrusion detection systems and predictive models to mitigate and prevent DDoS attacks. The use of the PCAP format facilitates the import of the data into various research software platforms.
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Registered trials
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