L-DIT: A dApp for Live Detectability, Identifiability and Trackability for ASOs on the Behavioral Dynamics Blockchain
Anirban Chowdhury, Yasir Latif, Moriba K. Jah, Samya Bagchi

TL;DR
This paper introduces L-DIT, a blockchain-based dApp that provides a universal, transparent scoring system for space objects' detectability, identifiability, and trackability, enhancing space safety and sustainability without sensitive data sharing.
Contribution
The work presents a novel L-DIT scoring system implemented on the Behavioral Dynamics blockchain, enabling holistic, cross-entity assessment of ASOs regardless of geopolitical boundaries.
Findings
L-DIT score can be applied to all ASOs using blockchain data.
The system enables comparison of ASOs' sustainability scores across different entities.
The approach enhances space situational awareness and supports regulatory compliance.
Abstract
As the number of Anthropogenic Space Objects (ASOs) grows, there is an urgent need to ensure space safety, security, and sustainability (S3) for long-term space use. Currently, no globally effective method can quantify the safety, security, and Sustainability of all ASOs in orbit. Existing methods such as the Space Sustainability Rating (SSR) rely on volunteering private information to provide sustainability ratings. However, the need for such sensitive data might prove to be a barrier to adoption for space entities. For effective comparison of ASOs, the rating mechanism should apply to all ASOs, even retroactively, so that the sustainability of a single ASO can be assessed holistically. Lastly, geopolitical boundaries and alignments play a crucial and limiting role in a volunteered rating system, limiting the space safety, security, and sustainability. This work presents a Live…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Anomaly Detection Techniques and Applications
