Detecting vulnerability in network systems through AI York University researchers are exploring how to better secure a digital world increasingly shaped by the Internet of Things (IoT) by understanding how malicious bots operate and developing stronger defences against them. IoT devices are everyday objects that connect to the internet so they can send, receive and […]
Celebrating Sepideh’s DAAD Research Grant Achievement Congratulations to our PhD student Sepideh HajiHosseinKhani on receiving the prestigious DAAD Research Grant. She will be joining the Institute for Data Science, Cloud Computing and IT Security (IDACUS) at Furtwangen University in Germany to advance her research on secure AI and decentralized finance. This achievement reflects her excellent […]
How York researchers are strengthening cybersecurity York University researchers are exploring how to better secure a digital world increasingly shaped by the Internet of Things (IoT) by understanding how malicious bots operate and developing stronger defences against them. IoT devices are everyday objects that connect to the internet so they can send, receive and act […]
Unveiling malicious PDF behavior: Interpretable classification and profiling of malicious PDF using TabNet With the inevitable growth of information digitization, Portable Document Format (PDF) has become one of the most popular exploited file formats for document exchange among various applications and platforms. Consequently, PDF files have become an attractive target for attackers to infect and […]
Unveiling intruders’ behaviors: explainable AI-based profiling of malicious bot activities in IoT networks The rapid proliferation of Internet of Things (IoT) devices has improved connectivity but introduced new cybersecurity risks, particularly from botnets. Detecting and identifying malicious botnet activities is crucial for early attack mitigation, understanding attack patterns, and deploying effective countermeasures. However, state-of-the-art IoT […]
MQTTFlowLyzer: interpretable TabNet-based flow-level MQTT intrusion detection for IoT MQTT is widely used in IoT systems but remains vulnerable due to its lightweight design. This paper proposes an interpretable deep learning-based intrusion detection framework that processes raw PCAP data through flow-based analysis. It introduces MQTTFlowLyzer for extracting protocol-aware features and presents the BCCC-IoT-MQTT-IDS-2025 dataset, which […]
CAN-BiGRUBERT: Unveiling Automotive Vehicle Intruders by Profiling and Characterizing Anomalies in Controller Area Network In-vehicle Controller Area Networks (CAN) are vulnerable to various injection attacks that can compromise the safety of vehicle occupants and result in financial losses. While a substantial body of work on CAN intrusion detection exists, it lacks multiclass attack classification models. […]
A deep learning-based vulnerability detection in blockchain smart contracts using masked attention and control flow graph analysis SCs are self-executing programs on the blockchain, used for transactions without intermediaries, particularly in cryptocurrencies like Ethereum. However, they are vulnerable to security flaws that can lead to significant financial losses, as demonstrated by the DAO hack 2016. […]
Toward generating a large-scale IoT-Zwave intrusion detection dataset: Smart device profiling, intruders behavior, and traffic characterization This article introduces BCCC-IoT-IDS-Zwave-2025, the most extensive and diverse IoT smart home dataset to date, developed over five months using a large-scale testbed comprising more than 50 IoT devices and encompassing over 80 distinct attack scenarios. Unlike prior datasets […]
BCCC, York University, Toronto, ON, Canada The second CyberSecurity Cartoon Award (CSCA) – Hosted by Universidad Politécnica de Madrid (Spain) Today, October 6, We’re excited to announce the official winners of the second CyberSecurity Cartoon Award (CSCA 2025); a flagship initiative under the Understanding Cybersecurity Series (UCS) program, dedicated to promoting cybersecurity awareness among K-12 […]