Security

a Sinkhole attack in a dataset, we'll generate data that typically reflects network traffic and interactions, where some nodes act as sinkholes by attracting all or most of the traffic due to malicious intent. Here's how I'll structure the dataset for 80,000 records:

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a dataset with 50,000 records simulating a Sybil attack scenario. Here's the plan for each record in the dataset:

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322 Views

An IEEE 802.15.4 backscatter communication dataset for Radio Frequency (RF) fingerprinting purposes.

It includes I/Q samples of transmitted frames from six carrier emitters, including two USRP B210 devices (labeled as c#) and four CC2538 chips (labeled as cc#), alongside ten backscatter tags (identified as tag#). The carrier emitters generate an unmodulated carrier signal, while the backscatter tags employ QPSK modulation within the 2.4 GHz frequency band, adhering to the IEEE 802.15.4 protocol standards.

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418 Views

X-CANIDS Dataset (In-Vehicle Signal Dataset)

In March 2024, one of our recent research "X-CANIDS: Signal-Aware Explainable Intrusion Detection System for Controller Area Network-Based In-Vehicle Network" was published in IEEE Transactions on Vehicular Technology. Here we publish the dataset used in the article. We hope our dataset facilitates further research using deserialized signals as well as raw CAN messages.

Real-world data collection. Our benign driving dataset is unique in that it has been collected from real-world environments.

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This dataset comprises audio recordings of ultra-high-frequency ambient noise stored in the lossless waveform format (WAW). The recordings were sampled at a frequency sample rate of 2.048 MHz and then provided at a downsampled audio rate of 48 kHz for compatibility and practical usage. The total length of the dataset is 01:30:29, consisting of approximately 260 million data points. (2024-03-30)

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This dataset is associated with the injection of false data into solar-powered insecticidal lamps, primarily aimed at reporting false data injection attacks on the Solar insecticidal lamps-Internet of Things (SIL-IoTs). The data was collected on the campus of Nanjing Agricultural University, gathering two types of data from the insecticidal lamp device of Chengdu Biang Technology Co., Ltd. and our team's self-developed insecticidal lamp device (insect count and sound signal data, respectively). The insect count data is in text format and has not been processed.

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Image representation of Malware-benign dataset. The Dataset were compiled from various sources malware repositories:  The Malware-Repo, TheZoo,Malware Bazar, Malware Database, TekDefense. Meanwhile benign samples were sourced from system application of Microsoft 10 and 11, as well as open source software repository such as Sourceforge, PortableFreeware, CNET, FileForum. The samples were validated by scanning them using Virustotal Malware scanning services. The Samples were pre-processed by transforming the malware binary into grayscale images following rules from Nataraj (2011).

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In today's world of online communication and digital media, hate speech has become an alarming problem worldwide. With the advancement of the internet, while people enjoy numerous benefits, there's also a dark side where individuals are subjected to horrendous bullying through hate speech. Tragically, some instances even lead to extreme actions like suicide or self-destructive behavior.

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419 Views

The results are based on the measurements conducted on small drones and a bionic bird using a 60 GHz millimeter wave radar, analyzing their micro-Doppler characteristics in both time and frequency domain. The results are presented in .pkl format. The more detailed description of the data and how the authors processed it will be updated soon.

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1065 Views

This dataset presents real-world IoT device traffic captured under a scenario termed "Active," reflecting typical usage patterns encountered by everyday users. Our methodology emphasizes the collection of authentic data, employing rigorous testing and system evaluations to ensure fidelity to real-world conditions while minimizing noise and irrelevant capture.

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