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To tackle the challenge of enhancing cybersecurity resiliency on a broader scale, it is essential to collaborate with the industry and employ innovative research methods to develop efficient and relevant tools while promoting public education and awareness. As part of the Understanding Cybersecurity Series (UCS) program at BCCC, we strive to gather, define, and impart fundamental knowledge and understanding to the general public in a manner that is comprehensible, accessible, and inclusive. We aim to support the education and training of IT systems and cybersecurity students, academics, researchers, developers, and industry professionals while disseminating some of the more easily understandable and applicable research findings to the broader community.

Understanding Cybersecurity Series (UCS) knowledge mobilization annual bulletins:

First Bulletin (Cybersecurity month - 2024)

Unveiling the UCS Cybersecurity Package: USC Bulletin 01-2024 (PDF)

Articles


Unveiling Evasive Malware Behavior: Towards Generating a Multi-Sources Benchmark Dataset and Evasive Malware Behavior Profiling Using Network Traffic and Memory Analysis

Arash Habibi Lashkari1, MohammadMoein Shafi, Yongkun Li, Abhay Pratap Singh, Ashley Barkworth, The Journal of Supercomputing, 2025


Unveiling Smart Contracts Vulnerabilities: Toward Profiling Smart Contracts Vulnerabilities using Enhanced Genetic Algorithm and Generating Benchmark Dataset

Sepideh HajiHosseinKhani, Arash Habibi Lashkari, Ali Mizani Oskui, Blockchain: Research and Applications, December 2024, 100253

Toward Generating a Large Scale Intrusion Detection Dataset and Intruders Behavioral Profiling using Network and Transportation Layers Traffic Flow Analyzer

Moein Shafi, Arash Habibi Lashkari, A.H. & Arousha Haghighian Roudsari, Journal of Netw System Management Vol. 33, 44 (2025)

A comprehensive survey of smart contracts vulnerability detection tools: Techniques and methodologies

Niosha Hejazi, Arash Habibi Lashkari, Journal of Network and Computer Applications, Volume 237,
2025, 104142


NTLFlowLyzer: Toward generating an intrusion detection dataset and intruder behavior profiling through network layer traffic analysis and pattern extraction

MohammadMoein Shafi, Arash Habibi Lashkari, Arousha Haghighian Roudsari, Computers & Security, 2025, 104160, ISSN 0167-4048

Unveiling Malicious DNS Behavior Profiling and Generating Benchmark Dataset through Application Layer Traffic Analysis

MohammadMoein Shafi, Arash Habibi Lashkari, Hardhik Mohanty, Computers and Electrical Engineering, Volume 118, Part B, September 2024


IoT malware: An attribute-based taxonomy, detection mechanisms and challenges

Princy Victor, Arash Habibi Lashkari, Rongxing Lu, Tinshu Sasi, Pulei Xiong & Shahrear Iqbal, Peer-to-Peer Networking and Applications, Vol 16, pages1380–1431(2023)

Robust stacking ensemble model for darknet traffic classification under adversarial settings

Hardhik Mohanty, Arousha Haghighian Roudsari and Arash Habibi Lashkari, Computers & Security Journal, Vol 120, 2022

Unveiling Vulnerable Smart Contracts: Toward Profiling Vulnerable Smart Contracts using Genetic Algorithm and Generating Benchmark Dataset

Sepideh HajiHosseinKhani, Arash Habibi Lashkari, Ali Mizani Oskui, Blockchain: Research and Applications, Vol. 4 (2023)


Unveiling DoH Tunnel: Toward Generating a Balanced DoH EncryptedTraffic Dataset and Profiling malicious Behaviour using InherentlyInterpretable Machine Learning

Sepideh Niktabe, Arash Habibi Lashkari, Arousha Haghighian Roudsari, Peer-to-Peer Networking and Applications, Vol. 17 (2023)

A comprehensive survey on IoT attacks: Taxonomy, detection mechanisms and challenges

Tinshu Sasi, Arash Habibi Lashkari, Rongxing Lu, Pulei Xiong, Shahrear Iqbal, Journal of Information and Intelligence (2023)

Detection, Characterization and Profiling DOH Malicious Traffic Using Statistical Pattern Recognition

Sepideh Niktabe, Arash Habibi Lashkari, Dilli Prasad Sharma, International Journal of Information Security, Vol. 22, (2023)