Network and Transportation Layers Flow Analyzer (NTLFlowLyzer) We released the first version of NTLFlowLyzer tool as a Python open-source project to extract Network and Transportation layers features from network traffic for Anomaly Profiling (AP).
Benign User Profiler (BUP) We released the first version of Benign User Profiler (BUP) tool for generating network traffic based on the benign user behavior to create the background traffic for anomaly detection research project on network security.
Toward Generating a New Cloud-Based Distributed Denial of Service (DDoS) Dataset and Cloud Intrusion Traffic Characterization.
The Smart Contracts Vulnerability Analyzer (SCsVulLyzer) is a Python-based tool designed to analyze and extract key metrics from Ethereum smart contracts written in Solidity. It employs a suite of functions to dissect the contract's source code, compiling it to obtain its abstract syntax tree (AST), bytecode, and opcodes. The analyzer calculates entropy of the bytecode […]
BCCC-VulSCs-2023 We released the 'BCCC-VulSCs-2023' dataset to analyze the secure and vulnerable Smart Contracts. The BCCC-VulSCs-2023 dataset is a substantial collection for Solidity Smart Contracts (SCs) analysis, comprising 36,670 samples, each enriched with 70 feature columns. Dataset: BCCC-VulSCs-2023
Research Article Unveiling vulnerable smart contracts: Toward profiling vulnerable smart contracts using genetic algorithm and generating benchmark dataset
MacEwan University, Edmunton, Alberta, Canada (Feb 2024) Cybersecurity for All: Raising Awareness Across the Digital Landscape Elevate your cybersecurity awareness with our Understanding Cybersecurity (UCS) seminar series. Designed for students, researchers, and Developers, UCS provides essential knowledge and skills to tackle cyber threats effectively. Join us and boost your cybersecurity vigilance! Delivering another seminar from […]
BCCC-CIRA-CIC-DoHBrw-2020 We released the 'BCCC-CIRA-CIC-DoHBrw-2020' dataset to address the imbalance in the 'CIRA-CIC-DoBre-2020' dataset. Unlike the 'CIRA-CIC-DoHBrw-2020' dataset, which is skewed with about 90% malicious and only 10% benign Domain over HTTPS (DoH) network traffic, the 'BCCC-CIRA-CIC-DoHBrw-2020' dataset offers a more balanced composition including 249,836 instances in each category. Dataset: BCCC-CIRA-CIC-DoHBrw-2020
Cybersecurity Month, October 2023 Cybersecurity for All: Raising Awareness Across the Digital Landscape In recognition of Cybersecurity Month, we proudly present our research center's (BCCC) commitment to enhancing public safety and awareness through the innovative Understanding Cybersecurity Series (UCS) Research Program at the York Circle annual event. Join us on a journey of navigating the […]
Cybersecurity Workshop The Understanding Cybersecurity Series (UCS) is a comprehensive knowledge mobilization program aimed at addressing the critical issue of cybersecurity resiliency on a broader scale founded by Professor Arash Habibi Lashkari at the School of Information Technology in York. It operates under the premise that tackling cybersecurity challenges effectively requires creating efficient and relevant […]