Encrypted Computation of Collision Probability for Secure Satellite Conjunction Analysis
Journal:
arXiv
Published Date:
Jan 13, 2025
Abstract
The computation of collision probability ($\mathcal{P}_c$) is crucial for
space environmentalism and sustainability by providing decision-making
knowledge that can prevent collisions between anthropogenic space objects.
However, the accuracy and precision of $\mathcal{P}_c$ computations is often
compromised by limitations in computational resources and data availability.
While significant improvements have been made in the computational aspects, the
rising concerns regarding the privacy of collaborative data sharing can be a
major limiting factor in the future conjunction analysis and risk assessment,
especially as the space environment grows increasingly privatized, competitive,
and fraught with conflicting strategic interests. This paper argues that the
importance of privacy measures in space situational awareness (SSA) is
underappreciated, and regulatory and compliance measures currently in place are
not sufficient by themselves, presenting a significant gap.
To address this gap, we introduce a novel encrypted architecture that
leverages advanced cryptographic techniques, including homomorphic encryption
(HE) and multi-party computation (MPC), to safeguard the privacy of entities
computing space sustainability metrics, inter alia, $\mathcal{P}_c$. Our
proposed protocol, Encrypted $\mathcal{P}_c$, integrates the Monte Carlo
estimation algorithm with cryptographic solutions, enabling secure collision
probability computation without exposing sensitive or proprietary information.
This research advances secure conjunction analysis by developing a secure MPC
protocol for $\mathcal{P}_c$ computation and highlights the need for innovative
protocols to ensure a more secure and cooperative SSA landscape.
