SESAIS Research Lab

The Software Engineering for Secure AI-based Systems (SESAIS) Research Lab, led by Dr. Torre at the University of Washington Tacoma, focuses on enhancing the security, reliability, and trustworthiness of AI-driven software systems. Our research emphasizes critical areas including autonomous systems such as drones and IoT devices, addressing vulnerabilities through innovative cybersecurity techniques. By collaborating with leading academic institutions, industry partners, and government agencies, SESAIS aims to solve emerging cybersecurity challenges, paving the way for robust, resilient, and secure technologies in increasingly interconnected environments.

Research Area

AI-Driven Cybersecurity: Developing AI-powered Intrusion Detection Systems to identify and mitigate cyber threats in autonomous systems.
Privacy-Preserving Machine Learning: Enhancing federated learning techniques to ensure data privacy while maintaining robust performance in intrusion detection systems.
Model-Driven Engineering: Utilizing model-based approaches to improve the design and analysis of complex software systems, ensuring consistency and reliability.

What's New in the Lab

The paper "Toward Enhancing Privacy Preservation of a Federated Learning CNN Intrusion Detection System in IoT: Method and Empirical Study" has been accepted to the Journal First Track at the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) 2025.

The paper "Toward Real-Time Intrusion Detection for Autonomous Vehicles: A Vision for Deep Learning-Based Security Frameworks" has been accepted to the Vision and Emerging Results Track at ESEM 2025.

End of the Quarter Colloquium – Spring 2025: Jacob Klymenko presented the results of his research on security attacks targeting autonomous drones.

Students Involvement

The SESAIS Lab actively engages students in cutting-edge research projects. I am seeking highly motivated students to join our research group through the Ph.D. program in Computer Science and Systems at the University of Washington Tacoma. Ideal candidates should hold a bachelor's degree and have a strong interest in AI-driven cybersecurity research. If you are interested, please email me your CV and a brief research statement. Additionally, motivated undergraduate and master's students at UW Tacoma are warmly invited to participate in ongoing research projects under my supervision.

Current Students:

Xiaoling Wei (Incoming), PhD CSS. Research Topic: Security of Autonomous Systems (TBD).

Kannika Armstrong, Master CSS. Research Topic: Optimizing Performance and Efficiency of Lattice-Based Post-Quantum Cryptography Algorithms in Resource-Constrained UAV Environments.

Ruslan Ivanovich Nurimbetov, Master CSS. Research Topic: Federated Learning Techniques to Enhance Security in UAVs.

Noah Ogilvie, Undergraduate CSS. Research Topic: Development of an Intrusion Detection System for Autonomous Drones Using Public Datasets.

Graduated Students:

Jacob Klymenko, Undergraduate CSS. Research Topic: Security Attacks on Autonomous Drones. (2024-2025)

Academic and Industry Collaboration

Below is a list of faculty members and idustry induviduals with whom there is ongoing research collaboration:

Davide Fucci, Associate Professor, Blekinge Institute of Technology, Sweden.

Mohammad Jasim, Assistant Professor, University of Washington Tacoma, USA.

Claudio Menghi, Asssociate Professor, University of Bergamo, Italy.

Amirpasha Javid, Director Research Partnerships, Quanser Consulting Inc., Canada.