Cybersecurity in Space Domain Awareness and Exploration - College of Engineering - Purdue University

Project Description

Space operations have long been led by governmental space agencies (e.g., NASA and international partners) and established space companies. Today, however, the entry of startup companies and newly spacefaring nations is rapidly increasing space traffic and adding new layers of complexity. This growth raises urgent challenges for secure information sharing, negotiation, and cooperation in space.

This project will advance the theory, methods, and algorithms for space cybersecurity. By integrating cryptographic techniques such as multi-party computation and homomorphic encryption with control theory and astrodynamics, this project enables a privacy-preserving collaborative space ecosystem. Furthermore, the project will explore proofs of compliance and transparency logs for space operations without revealing sensitive data through cryptographic zero-knowledge proofs and commitment schemes.

The project will build on recent studies (e.g., Ref.1) on privacy-preserving collision risk assessment to address challenges in maneuver planning under information-sharing constraints. The research will extend these methods to support autonomous, uncertainty-aware multi-spacecraft operations under cybersecurity constraints, leveraging recent studies on spacecraft autonomy and secure controller design (e.g., Ref. 2, 3). Finally, the project will build on recent work (e.g., Ref. 4, 5) to create solutions for data provenance and enable auditable chains of operation in space without disclosing private information.

Start Date

Spring/Summer/Fall 2027

Postdoc Qualifications

Successful candidates must hold a Ph.D. in Aerospace Engineering, Electrical Engineering, Computer Science, or in a related area by the date of the position start, with a strong interest in the security of cyber-physical systems for space applications. Prior experience in one or more of the following areas is required: information theory, machine learning, control theory, and astrodynamics.

Co-advisors

Kenshiro Oguri, koguri@purdue.edu, AAE, URL: https://engineering.purdue.edu/OguriGroup
Zahra Ghodsi, zahra@purdue.edu, ECE, URL: https://engineering.purdue.edu/ECE/People/ptProfile?resource_id=270860 

Bibliography

J. Suh, M. Hibbard, K. Teranishi, T. Tanaka, M. Jah, and M. Akella, “Encrypted computation of collision probability for secure satellite conjunction analysis,” International Astronautical Congress (IAC), 2024.

K. Oguri, “Chance-Constrained Control for Safe Spacecraft Autonomy: Convex Programming Approach,” American Control Conference (ACC), 2024.

K. Teranishi and T. Tanaka, "Client-Aided Secure Two-Party Computation of Dynamic Controllers," The IEEE Transactions on Control of Network Systems, 2025

G. Almashaqbeh and Z. Ghodsi, “AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning,” Privacy Enhancing Technologies Symposium (PETS), 2025.

A. Gan and Z. Ghodsi, “Sentry: Authenticating machine learning artifacts on the fly,” Conference on Computer and Communications Security (CCS), 2025.