Below is a list of open BSc and MSc thesis topics across my main research areas. Most topics can be tailored to either a Bachelor's or Master's level.
If you want to discuss any of these topics (or propose your own idea( email me at federico.coro@unipd.it with a brief note about your background and interests.
Secure and Attack-Resilient Routing in LEO Satellite Constellations (MSc / BSc)
Description: Low Earth Orbit (LEO) mega-constellations rely on dynamic Inter-Satellite Links (ISLs) and ground-to-space relays to route traffic globally, making them vulnerable to wormhole, blackhole, and time-delay attacks. This thesis investigates graph-theoretic and algorithmic routing protocols that detect compromised nodes and dynamically reroute packets under strict latency and onboard energy constraints.
Skills: Graph algorithms, network security, Python/C++ or network simulators (e.g., Hypatia, ns-3).
Anti-Spoofing and Resilient Positioning for Satellites and Spaceborne Receivers (MSc)
Description: GNSS spoofing, signal jamming, and falsified TLE (Two-Line Element) ephemeris data can deceive satellite navigation and ground-station tracking systems. This project focuses on designing and evaluating cooperative localization and physical-layer verification schemes (leveraging Doppler shift, Time Difference of Arrival, or cross-link ranging) to guarantee trustworthy positioning in contested environments.
Skills: Wireless security, signal/positioning models, Python/MATLAB.
Lightweight Authentication and Key Management for Resource-Constrained CubeSats (MSc / BSc)
Description: CubeSats operate with tight power, memory, and compute budgets, making traditional heavyweight cryptographic handshakes impractical during brief ground-station contact windows or rapid inter-satellite handovers. Building on serverless and lightweight protocol designs, this thesis aims to design, implement, and benchmark a resilient authentication and group key-sharing protocol tailored for CubeSat swarms.
Skills: Applied cryptography, security protocols, C/Python or embedded platforms.
Analyzing and Enhancing FIDO2/WebAuthn Resilience in Distributed Ecosystems (MSc / BSc)
Description: FIDO2 and WebAuthn standards provide robust passwordless authentication via public-key cryptography, yet managing cross-device credentials, passkey synchronization, and roaming authenticators introduces new edge-case attack surfaces (e.g., session hijacking, relay attacks, or authenticator impersonation). This thesis investigates vulnerabilities in passwordless deployments and proposes hardening strategies for multi-device or enterprise environments.
Skills: Cryptographic protocols, web security, authentication mechanisms (OAuth2/FIDO2).
Lightweight FIDO-Based Authentication for IoT and Edge Devices (MSc)
Description: Extending modern passwordless authentication paradigms down to resource-constrained IoT nodes and microcontrollers. The goal is to design an optimized, low-overhead cryptographic challenge-response mechanism inspired by FIDO specifications that operates efficiently without heavy TPM hardware dependencies.
Skills: Applied cryptography, embedded systems security, C/Python.
Distributed LLM-Powered Human-Swarm Interaction in Resource-Constrained UAV Networks (MSc)
Description: Connected to our funded 2026–2027 BIRD research project, this thesis explores how lightweight or quantized Large Language Models (LLMs) and edge inference can translate high-level human operator intent into distributed, safety-verified task plans for autonomous UAV swarms operating under bandwidth and energy limits.
Skills: Python, LLMs/Edge AI, distributed systems, multi-agent coordination.
GPS-Denied Swarm Navigation & Anti-Spoofing Defense Protocols (MSc / BSc)
Description: Drone swarms operating in adversarial or GNSS-compromised environments must maintain formation, coverage, and connectivity without relying on trusted satellite navigation. Possible directions include extending RSSI-based anti-spoofing defenses, virtual spring-damper self-healing topologies, or Crazyflie nano-drone testbed implementations.
Skills: Wireless networks, distributed algorithms, Python/ROS/Crazyflie ecosystem.
Autonomous Swarm Navigation in BVLOS via Reinforcement Learning (MSc)
Description: This thesis applies Reinforcement Learning (RL) to enable autonomous flight of drone swarms in Beyond-Visual-Line-of-Sight (BVLOS) scenarios. The objective is to devise and train a policy that accomplishes coverage or delivery tasks while avoiding high-risk ground zones, preventing collisions, and maintaining reliable ground connectivity.
Skills: Reinforcement Learning (PyTorch/Gymnasium), Python, path planning.
Defending Federated Learning Against Targeted and Collusive Poisoning Attacks (MSc)
Description: Federated Learning (FL) enables decentralized model training without sharing raw data, but remains vulnerable to coordinated model-poisoning and backdoor attacks. Building on our recent defense frameworks (FedDOT), this thesis focuses on designing and benchmarking robust aggregation and graph-based anomaly detection mechanisms against adaptive, colluding adversaries.
Skills: Machine Learning (PyTorch/Flower), cybersecurity, Python.
Battery-Aware and Sustainable Federated Learning at the Edge (MSc / BSc)
Description: Mobile and IoT clients participating in Federated Learning face strict energy budgets. Extending our BatteryFL framework, this thesis explores client selection and model compression strategies that jointly optimize global model accuracy, fairness, and battery longevity across heterogeneous edge devices.
Skills: Python, Federated Learning frameworks, optimization.
Energy-Aware Eternal Vertex Cover & Graph Protection Games (MSc / BSc)
Description: The Eternal Vertex Cover (EVC) problem models an infinite attacker–defender game on a graph, where mobile guards reconfigure across vertices to defend against sequential edge attacks.
Theoretical Track (MSc): Investigate energy-aware variants, bounds, and approximation algorithms on specific graph classes for persistent UAV surveillance.
Implementation Track (BSc): Develop an interactive web-based EVC visualizer and solver where users can build custom graphs, simulate attacker–defender strategies step-by-step, and inspect guard trajectories in real time.
Skills: Graph theory and algorithms (MSc); JavaScript/TypeScript or Python visualization libraries (BSc).
Online Mining of Frequent Itemsets in Data Streams (BSc / MSc)
Description: Identifying frequent patterns in high-velocity streaming data is a core problem in network traffic monitoring and data mining. This thesis involves designing, implementing, and benchmarking memory-efficient streaming algorithms against state-of-the-art baselines on real-world datasets.
Skills: Algorithms and data structures, Python/C++/Rust.