Overview

Brian's research interests primarily reside in the areas of anomaly detection and various types of security assessments. Past and current graduate students and their research projects, undergraduate design projects and publications are listed below.

Current Graduate Students

  • Josh Franks (co-supervision with Dr. Tom Dean, Queen's) - Anomaly Detection
  • Cody Carter - Research TBD
  • Aromi Adebayo - Research TBD
  • Mike Kim - Anomaly Detection
  • Dain Saulnier (co-supervision with Dr. Roberge) - MIL-STD-1553B Flight Mode Classification
  • Patricia Watkins - Fuzzing/Vulnerability Discovery
  • Sébastien Généreux (co-supervision with Dr. Roberge) - Syntax-Aware Greybox Protocol Fuzzing
  • Saige Mukherjee - MIL-STD-1553B, Schedule, RT and Dataset Development
  • Jacob Hickling (co-supervision with Dr. Tom Dean) - Vulnerability Discovery (Queen's)
  • Stéphane Gagnon - Host Based Anomaly Detection Using Temporal Graph Autoencoder and Sysmon Logs

Past Graduate Students

  • 2025, Rachael Machnee - Windows Binary Fuzzing with Code Coverage
  • 2024, Andrew Fryer (supporting supervisor with Dr. Tom Dean, Queen's University) - Binary Grammars for Blackbox Fuzzing
  • 2023, Clint Legg (co-supervision with Dr. Roberge) - Exposing Vulnerabilities in a Proprietary SCADA System
  • 2023, Charlie Grimshaw - Link-Based Anomaly Detection with SysMon and Graph Neural Networks
  • 2023, Emilie Coote - Natural Language Processing and Deep Learning for IPMS Host-Based Anomaly Detection
  • 2023, Alec Harlow (co-supervision with Dr. Roberge) - Anomaly Detection for the MIL-STD-1553B Multiplex Data Bus Using an LSTM Autoencoder
  • 2022, Taylor Perkins (co-supervision with Dr. Leblanc) - Data Handling Framework to Enable IPMS Anomaly Detection
  • 2022, Patrick Cousineau - IPMS Vulnerability Discovery Through Network Protocol Fuzzing
  • 2022, Dakotah Soucy - Feature Engineering for a MIL-STD-1553B LSTM Autoencoder Anomaly Detector
  • 2021, Eddie O'Handley - Physical Layer Security of the ARINC 429 Data Bus Protocol
  • 2020, Jon Timmins (co-supervision with Dr. Knight) - Offensive Cybersecurity Trainer for the Integrated Platform Management System

4th Year Design Projects

  • 2024/2025 (Co-supervision with Maj Mark Adams) - Kate Lee, Braden Kessler, Mikhael Zavala-Thyer - Audimus Project, CUBESAT Arctic Mission
  • 2023 (co-supervision with Dr. Roberge) - Grant Brooks and Jake Giczi, MIL-STD-1553B Data Bus Attack Framework
  • 2020 - Bill Lai and Han Na Baik, Custom ELK Stack for Anomaly Detection leveraging Suricata and Zeek
  • 2019 (co-supervision with Dr. Leblanc) - Cody Carter, Ryan Tsui and Connor Weeks, Instrusion Detecton System for NISRN

Publications

Conference Publications
  • J. Lord, S. Knight, B. Lachine, "Cyber Defence Trainer for Marine Integrated Platform Management Systems", 2025 European Conference on Cyber Warfare and Security, Kaiserslautern, Germany, 2025, pp. 357-366, https://doi.org/10.34190/eccws.24.1.3333.
  • T. Perkins and B. Lachine, "A Time-Series and Density-Based Filter for DNS Log Reduction and Analysis," 2024 IEEE International Conference on Cyber Security and Resilience (CSR), London, United Kingdom, 2024, pp. 303-308, doi: 10.1109/CSR61664.2024.10679388.
  • D. Soucy, B. Lachine, "Feature Engineering for a MIL-STD-1553B LSTM AutoEncoder", 2024 European Conference on Cyber Warfare and Security (ECCWS), University of Jyväskylä, Jyväskylä Finland, pp. 528-537, doi: https://doi.org/10.34190/eccws.23.1.2101.
  • A. Harlow, B. Lachine, V. Roberge, "Anomaly Detection for the MIL-STD-1553B Multiplex Data Bus Using an LSTM Autoencoder", 2024 International Conference on Cyber Warfare and Security (ICCWS), Johannesburg, South Africa, pp. 103-111, doi: https://doi.org/10.34190/iccws.19.1.1974.
  • C. Grimshaw, B. Lachine, T. Perkins and E. Coote, "Link-based Anomaly Detection with Sysmon and Graph Neural Networks," 2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC), Houston, TX, USA, 2024, pp. 1-6, doi: 10.1109/ICAIC60265.2024.10433846.
  • R. Al Mallah, B. Lachine and G. Badu-Marfo, "Security of SDN in an Adversarial Setting: The DDoS Case," 2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), Dubai, United Arab Emirates, 2023, pp. 53-58, doi: 10.1109/GCAIoT61060.2023.10385112.
  • A. Fryer, T. Dean, and B. Lachine, “Input Output Grammar Coverage in Fuzzing”, 2023 IEEE Military Communications Conference (MILCOM), Oct. 2023, Boston, MA, USA, pp. 937–943. doi: 10.1109/MILCOM58377.2023.10356308.
  • E. Coote and B. Lachine, “Platform Management System Host-Based Anomaly Detection using TF-IDF and an LSTM Autoencoder”, 2023 IEEE Military Communications Conference (MILCOM), Oct. 2023, Boston, MA, USA, pp. 471–477. doi: 10.1109/MILCOM58377.2023.10356381.
  • P. Cousineau and B. Lachine, "Enhancing Boofuzz Process Monitoring for Closed-Source SCADA System Fuzzing", 2023 IEEE International Systems Conference (SysCon), Vancouver, BC, Canada, 2023, pp. 1-8, doi: 10.1109/SysCon53073.2023.10131048.
  • J. Timmins, S. Knight and B. Lachine, "Offensive Cyber Security Trainer for Platform Management Systems", 2021 IEEE International Systems Conference (SysCon), Vancouver, BC, Canada, 2021, pp. 1-8, doi: 10.1109/SysCon48628.2021.9447060.
Technical Reports

Brian also has 13 technical reports submitted to research sponsors focused primarily on anomaly detection and fuzzing across information, operational and platform technologies.