Security
The advancements in the field of telecommunications have resulted in an increasing demand for robust, high-speed, and secure connections between User Equipment (UE) instances and the Data Network (DN). The implementation of the newly defined 3rd Generation Partnership Project 3GPP (3GPP) network architecture in the 5G Core (5GC) represents a significant leap towards fulfilling these demands. This architecture promises faster connectivity, low latency, higher data transfer rates, and improved network reliability.
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3285 Views
It is a real IoT traffic.
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79 Views
User's Behvoiur Scores with cyber attack victim as label
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313 Views
This project builds a length-versatile and noise-robust LoRa radio frequency fingerprint identification (RFFI) system. The LoRa signals are collected from 10 commercial-off-the-shelf LoRa devices, with the spreading factor (SF) set to 7, 8, 9, respectively. The packet preamble part and device labels are provided.
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1614 Views
Slow-rate DDoS attacks are recent threats targeting next-generation networks such as IoT, 5G, etc. Unlike conventional high-rate DDoS, slow-rate DDoS have not been deeply studied, mainly due to the limited number of existing datasets with real traces.
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2117 Views
This paper presents a real-time reconfigurable Cyber-Power Grid Operation Testbed (CPGrid-OT) with multi-vendor, industry-grade hardware, and software.
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915 Views
A comparative, empirical study of state-of-the-art contrastive and generative graph learning models applied to source and binary software fragments drawn from the National Vulnerability Database (NVD) reveals that Graph Masked Auto-Encoders show exceptional promise for detecting security vulnerabilities, outperforming all other baseline models in the study.
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4 Views
The data is a truth table of a 22-variable 4-resilient Boolean function with nonlinearity 2095616.
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113 Views
The dataset is available in GitHub and the link is given below:
https://github.com/sahilarora3117/capstone-19BCE1366-2023
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112 Views
This is a data set for Radio Frequency fingerprinting, which is a kind of identification of wireless devices based on their intrinsic physical features. The data set is composed by GSM bursts collected from 12 GSM mobile phones while transmitting. The samples have been collected using a Software Defined Radio with a sample rate at 20 MS/s. The content information has been removed from the bursts to remove the risk of bias due to content. The data set is in MATLAB format.
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974 Views