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Achieving Higher-Fidelity Conjunction Analyses Using Cryptography to Improve Information Sharing

Achieving Higher-Fidelity Conjunction Analyses Using Cryptography to Improve Information Sharing

Brett Hemenway
William Welser
Dave Baiocchi
Copyright Date: 2014
Published by: RAND Corporation
Pages: 66
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  • Book Info
    Achieving Higher-Fidelity Conjunction Analyses Using Cryptography to Improve Information Sharing
    Book Description:

    This report examines the feasibility of using modern cryptographic tools to improve space situational awareness. Specifically, the authors examine the applicability of secure multiparty computation (MPC) protocols as a means to compute the collision probability of two satellites. MPC protocols would provide satellite operators with a way to compute such “conjunction analyses” while maintaining the privacy of each operator’s orbital information.

    eISBN: 978-0-8330-8521-4
    Subjects: Technology

Table of Contents

  1. Front Matter
    (pp. i-ii)
  2. Preface
    (pp. iii-iv)
  3. Table of Contents
    (pp. v-vi)
  4. Figures
    (pp. vii-viii)
  5. Tables
    (pp. ix-x)
  6. Summary
    (pp. xi-xvi)
  7. Acknowledgments
    (pp. xvii-xviii)
  8. Abbreviations
    (pp. xix-xx)
  9. 1. Introduction
    (pp. 1-4)

    Since the launch of its first satellite in 1958, the United States has been interested in protecting its on-orbit assets. In order to maintain custody of its satellite inventory, and to predict and prevent collisions, the United States monitors the locations of objects in orbit. This monitoring is accomplished by the Space Surveillance Network (SSN), which is managed by U.S. Strategic Command (USSTRATCOM) and staffed by 14th Air Force. The SSN currently tracks more than 20,000 orbital objects larger than 10 cm in diameter, and the data provided by the SSN form the most important source of space situational awareness...

  10. 2. Overview of Secure Multiparty Computation
    (pp. 5-20)

    MPC is a cryptographic tool that allows a collection of stakeholders to compute any function of their private inputs while maintaining the secrecy of each individual’s input.¹ MPC protocols allow a collection of individuals to achieve anything that could be achieved in the presence of a trusted third party, but the trusted party is replaced by a transparent and provably secure cryptographic algorithm.

    Large-scale public tests of MPC protocols have been performed in the case of secure auctions, where each bidder can be sure of the privacy of his bid, yet confident that the winning bidder was chosen correctly, and...

  11. 3. Efficiency of Implementation
    (pp. 21-30)

    From a theoretical standpoint, cryptographers have known how to compute any function, including a conjunction analysis, securely using MPC protocols like Yao’s garbled circuit or the GMW protocol. The important question, however, is whether these computations can be performed efficiently enough to be of use in practice. If it takes days to perform a secure computation of a conjunction analysis, the data will be useless by the time the computation is finished. In the past, efficiency was the primary obstacle to the adoption of MPC protocols, but recent algorithmic and computational advances have improved the speed of MPC protocols to...

  12. 4. Conclusions and Recommendations
    (pp. 31-32)

    This research addressed the question of whether modern cryptographic tools can be used to improve SSA by facilitating secure conjunction analysis calculations without requiring operators to reveal their private orbital information to any outside party. Many cryptographic tools have been developed that allow multiple participants to engage in arbitrary secure computations. To be of value, however, a cryptographic protocol must be both secure and efficient enough to use in practice. Our analysis has focused on the efficiency of these protocols because the security of the underlying cryptographic algorithms has been rigorously and mathematically proven in the cryptographic literature.

    Our analysis...

  13. Appendix: Mathematical Background
    (pp. 33-40)
  14. Bibliography
    (pp. 41-46)