Security

SUNBURST Attack Dataset for Network Attack Detection

Overview:
The SUNBURST dataset is a unique and valuable resource for researchers studying network intrusion detection and prevention. This dataset provides real-world network traffic data related to SUNBURST, a sophisticated supply chain attack that exploited the SolarWinds Orion software. It focuses on the behavioral characteristics of the SUNBURST malware, enabling the development and evaluation of security mechanisms.

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Security and privacy are critical challenges in the rapidly evolving metaverse, which spans a variety of immersive applications, including virtual worlds, augmented reality, and lifelogging technologies.

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This dataset was developed using the MOBATSim simulator in MATLAB 2020b, designed to mimic real-world autonomous vehicle (AV) environments. It focuses on providing high-quality data for research in anomaly detection and cybersecurity, particularly addressing False Data Injection Attacks (FDIA). The dataset includes comprehensive sensor information, such as speed, rotational movements, positional coordinates, and labelled attack data, enabling supervised learning.

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Six vector maps are selected as experimental data. These maps are referred to as the coastline map, river map, building map, green land map, road map and waterway map, as shown in Fig. 9. The coastline map and river map, both in the China Geodetic Coordinate System 2000 (CGCS2000), can be downloaded from the website of the National Catalogue Service for Geographic Information of China (https://www.webmap.cn).

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This study analyzes and characterizes the relationship between human emotions and other elements (social bots and echo chambers), which are major factors in the spread of information, including disinformation and misinformation. The data set consists of a CSV file of posts that match the target word and period, and a database of the accounts that made the posts.

 

The following is a overall description of the objects and what the audience can expect to gain by downloading them.

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In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanismare utilized to characterize highly time-varying wireless channels.

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This paper conducts in-depth research on three text classification tasks: sentiment analysis, offensive language identification, and news topic classification.

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The 5G cellular technology has introduced advanced radio communication protocols and new frequency bands and enabled faster data exchange. These improvements increase network capacity and establish a foundation for high-bandwidth, low-latency services, helping the development of applications like the Internet of Things (IoT). However, information security poses significant challenges, particularly concerning attacks such as Fake Base Stations (FBS) and Stream Control Transmission Protocol (SCTP) Session Hijacking.

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This dataset contains signals collected from 10 commercial-off-the-shelf Wi-Fi devices by an USRP X310 equipped with four receiving antennas. It comprises signals affected by various channel conditions, which is intended for use by the researchers in the development of a channel-robust RFFI system. The preprocessed preamble segments, estimated CFO values and device labels are provided. Please refer to the README document for more detailed information about the dataset.

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Moving away from plain-text DNS communications,
users now have the option of using encrypted DNS protocols
for domain name resolutions. DNS-over-QUIC (DoQ) employs
QUIC—the latest transport protocol—for encrypted communi-
cations between users and their recursive DNS servers. QUIC is
also poised to become the foundation of our daily web browsing
experience by replacing TCP with HTTPP/3, the latest version
of the HTTP protocol.
Traditional TCP-based web browsing is vulnerable to website

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