Communications

The main goal of this research is to propose a realistic benchmark dataset to enable the development and evaluation of Internet of Medical Things (IoMT) security solutions. To accomplish this, 18 attacks were executed against an IoMT testbed composed of 40 IoMT devices (25 real devices and 15 simulated devices), considering the plurality of protocols used in healthcare (e.g., Wi-Fi, MQTT and Bluetooth).

This is the CSI data between the UAV and the base station in the ISAC system in an urban environment. It is generated by the raytracing module of sionna. It is used for UAV navigation.

Wi-Fi sensing has emerged as a promising non-intrusive approach for human activity recognition (HAR), leveraging the widespread availability of Wi-Fi-enabled devices. While machine learning tools help extract meaningful features from complex wireless propagation patterns, developing robust and domain-adaptive models remains challenging without diverse datasets.

Molecular Communications (MC), transferring information via chemical signals, holds promise for transformative healthcare applications within the Internet of Bio-Nano Things (IoBNT) framework. Despite promising advances toward practical MC systems, progress has been constrained by experimental testbeds that are costly, difficult to customize, and require labor-intensive fabrication.

This dataset comprises the time cost of ten cryptographic operations on our testing platform, as well as the required number of operations and corresponding time consumption at each phase of the authentication schemes from six selected literature sources. The data is utilized for comparative analysis and evaluation of the operational efficiency among various identity authentication schemes.

The source data files and code files of the paper: optical chaos shift keying communication system via neural network-based signal reconstruction. The following data is included:

1. Source figure file in the paper;

2. Source code of the proposed scheme, include the simulation code for communication, secure analysis and parameter mismatch range.

3. The source Simulink module is included for time-delayed chaotic signal generation.

A rapid growth of wireless communication networks, particularly in 5G Non-Standalone (NSA) deployments, has necessitated advanced multiple access techniques to enhance spectral efficiency, interference management, and energy optimization [1-3]. Rate-Splitting Multiple Access (RSMA) has arisen as a strong candidate to replace conventional Non-Orthogonal Multiple Access (NOMA) by efficiently splitting user data into common and private components. [1-2].

The CyberAlert-25 Dataset is a comprehensive collection of curated cyber threat data, developed to support advanced research in vulnerability detection, classification, and threat intelligence. Aggregated from authoritative sources such as the National Critical Information Infrastructure Protection Center (NCIIPC) and the MITRE Corporation, the dataset focuses on Common Vulnerabilities and Exposures (CVEs), encompassing a total of 29,650 entries.

<p>This dataset contains simulation results generated in OptiSystem for an 18‐tupling optical communication system. The parameters include optical source settings, modulator configurations, and a range of power and signal quality metrics. Key performance indicators—such as total power penalty (TPP), signal power penalty (SPP), and RMS jitter—are provided for each set of simulation inputs. The data are intended to facilitate reproducible research and to enable further analysis of high‐order frequency multiplication in optical networks.