Security
This dataset includes synthesized network configurations designed for evaluating network verifiers, spanning wide-area networks (WAN) and data center networks (DCN). For WAN, topologies range from 34 to 755 routers, derived from both direct selection and synthesis based on topologies from the Topology Zoo. Base configurations for each topology are generated following methodologies from prior studies. For DCN, configurations are based on the fat-tree architecture, adhering to RFC 7938 guidelines for BGP connectivity, with fat-tree structures ranging from 4-port to 20-port switches.
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This dataset contains original and augmented versions of the Korean Call Content Vishing (KorCCVi v2) dataset used in the study titled, "Enhancing Voice Phishing Detection Using Multilingual Back-Translation and SMOTE: An Empirical Study." The dataset addresses challenges of data imbalance and asymmetry in Korean voice phishing detection, leveraging data augmentation techniques such as multilingual back-translation (BT) with English, Chinese, and Japanese as intermediate languages, and Synthetic Minority Oversampling Technique (SMOTE).
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114 Views
This dataset contains a comprehensive V2X misbehavior dataset simulated using VASP, an open-source framework. VASP allows the simulation of diverse types of V2X attacks and works as a sub-module for Veins, a well-established open-source framework for running vehicular network simulations. Veins runs on an event-based network simulator OMNeT ++, and road traffic simulator SUMO. Data are collected from the Boston traffic network, which is a good candidate to represent real-world traffic mobility. We run VASP simulation for 3,000 simulated seconds to collect benign traces without any attacks.
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The data set includes attack implementations in an Internet of Things (IoT) context. The IoT nodes use Contiki-NG as their operating system and the data is collected from the Cooja simulation environment where a large number of network topologies are created. Blackhole and DIS-flooding attacks are implemented to attack the RPL routing protocol.
The datasets includes log file output from the Cooja simulator and a pre-processed feature set as input to an intrusion detection model.
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163 Views
This dataset used in the research paper "JamShield: A Machine Learning Detection System for Over-the-Air Jamming Attacks." The research was conducted by Ioannis Panitsas, Yagmur Yigit, Leandros Tassiulas, Leandros Maglaras, and Berk Canberk from Yale University and Edinburgh Napier University.
For any inquiries, please contact Ioannis Panitsas at ioannis.panitsas@yale.edu.
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139 Views
This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.
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1111 Views
Security patches play a crucial role in the battle
against Open Source Software (OSS) vulnerabilities. Meanwhile,
to facilitate the development of OSS projects, both upstream and
downstream developers often maintain multiple branches. Due
to the different code contexts among branches, multiple security
patch variants exist for the same vulnerability. Hence, to ease the
management of OSS vulnerabilities, locating all patch variants
of an OSS vulnerability is pretty important. However, existing
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46 Views
Intrusion detection in Unmanned Aerial Vehicle (UAV) networks is crucial for maintaining the security and integrity of autonomous operations. However, the effectiveness of intrusion detection systems (IDS) is often compromised by the scarcity and imbalance of available datasets, which limits the ability to train accurate and reliable machine learning models. To address these challenges, we present the "CTGAN-Enhanced Dataset for UAV Network Intrusion Detection", a meticulously curated and augmented dataset designed to improve the performance of IDS in UAV environments.
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667 Views
This dataset consists of network packet traces collected in 2023 on the 5G infrastructure deployed at Chalmers University of Technology.
The dataset includes 1,912 pcap files, distributed across 8 folders. Each pcap file captures 1 minute of encrypted network traffic generated by one of the following 8 popular mobile applications:
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410 Views
To provide a standardized approach for testing and benchmarking secure evaluation of transformer-based models, we developed the iDASH24 Homomorphic Encryption track dataset. This dataset is centered on protein sequence classification as the benchmark task. It includes a neural network model with a transformer architecture and a sample dataset, both used to build and evaluate secure evaluation strategies.
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127 Views