Dataset

UDP-QUIC Network Threat Dataset (BCCC-UDP-QUIC-IDS-2025)

Using UDPFlowLyzer and QUICFlowLyzer, the dataset provides a realistic cloud-based benchmark for UDP and QUIC intrusion detection research, specifically designed to analyze volumetric and application-specific UDP DDoS attacks in enterprise environments. The dataset combines realistic, benign organizational activities with multiple UDP attack campaigns executed over a multi-tier cloud infrastructure and captured through packet-level monitoring and […]

Malware Memory Snapshot and process-level behavioral Log Dataset (BCCC-MalMem-SnapLog-2025)

The dataset was systematically developed to capture memory-level behavioral dynamics of malware and benign processes through interval-based snapshot analysis. Unlike prior datasets that predominantly rely on static binaries or network-level observations, this dataset focuses on runtime memory behavior and process persistence, enabling a deeper understanding of how malicious activities evolve over time. It integrates diverse […]

IoT Bot Dataset (BCCC-Aposemat-IoT-BoT-2024)

The dataset was systematically developed by augmenting and refining the Aposemat-Bot-IoT-23 dataset to address limitations in class imbalance, labeling consistency, and feature representation. Unlike prior datasets that include limited or uneven distributions of malware families, this dataset focuses on high-quality botnet traffic and benign behavior, ensuring reliable and scalable modeling of IoT botnet activities. It […]

IoT MQTT IDS Dataset (BCCC-IoT-MQTT-IDS-2025)

The dataset was systematically developed by integrating and augmenting multiple high-quality MQTT-based intrusion detection datasets, enabling a comprehensive and protocol-aware representation of IoT communication. Unlike prior datasets that predominantly focus on packet-level or TCP-based analysis with limited consideration of application-layer semantics, this dataset captures rich MQTT behavioral patterns by leveraging protocol-aware feature extraction and diverse […]

Large-scale IoT-Zwave Intrusion Detection dataset (BCCC-IoT-IDS-Zwave-2025)

The BCCC-IoT-IDS-ZWave-2025 Dataset is a large-scale, multi-source IoT security dataset developed over five months (20 TB data, including more than 1 BILLION records) using a comprehensive smart-home testbed comprising more than 110 devices, including sensors, actuators, smart plugs, locks, meters, and controllers. According to the paper, the dataset includes 88 distinct attack scenarios spanning network-layer, […]

DeFi Fraud Transactions (BCCC-DeFiFraudTrans-2025)

BCCC-DeFiFraudTrans-2025 is a large-scale, Ethereum-based benchmark explicitly designed to profile fraudulent and legitimate DeFi transactions. It contains 1,026,867 annotated transaction samples spanning from 2017 to 2024, drawn from 9,374 unique wallet addresses. The dataset integrates wallet- and transaction-level attributes, with 79 features extracted using the DeFiTransLyzer-V1.0 analyzer. These features are organized into categories, including gas usage, cumulative gas consumption, token […]

Vulnerable Smart Contracts (BCCC-VulSCs-2023)

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. These features include the raw source code of the smart contract, a hashed version of the source code for secure referencing, and a binary label that indicates a contract as secure (0) or […]

Tabular IoT Attack Dataset (CIC-BCCC-NRC TabularIoTAttack-2024)

The CIC-BCCC-NRC TabularIoTAttack-2024 dataset is a comprehensive collection of IoT network traffic data generated as part of an advanced effort to create a reliable source for training and testing AI-powered IoT cybersecurity models. This dataset is designed to address modern challenges in detecting and identifying IoT-specific cyberattacks, offering a rich and diverse set of labeled […]

Malicious DNS and Attacks (BCCC-CIC-Bell-DNS-2024)

Using ALFlowLyzer, we successfully generated an augmented dataset, "BCCC-CIC-Bell-DNS-2024," from two existing datasets: "CIC-Bell-DNS-2021" and "CIC-Bell-DNS-EXF-2021." ALFlowLyzer enabled the extraction of essential flows from raw network traffic data, resulting in CSV files that integrate DNS metadata and application layer features. This new dataset combines light and heavy data exfiltration traffic into six unique sub-categories, providing […]

SQL Injection Attack (BCCC-SFU-SQLInj-2023)

This dataset consists of 11,012 evasive or sophisticated malicious SQL queries. These queries are generated using a genetic algorithm applied to the Kaggle malicious SQL dataset. The goal of the genetic algorithm is to enhance the evasiveness and sophistication of the original malicious queries. The full research paper outlining the details of the dataset and […]