William Welser

High-Precision Secure Computation of Satellite Collision Probabilities

The costs of designing, building, launching and maintaining satellites make satellite operators extremely motivated to protect their on-orbit assets. Unfortunately, privacy concerns present a serious barrier to coordination between different operators. One obstacle to improving safety arises because operators view the trajectories of their satellites as private, and refuse to share this private information with other operators. Without data-sharing, preventing collisions between satellites becomes a challenging task. A 2014 report from the RAND Corporation proposed using cryptographic tools from the domain of secure Multiparty Computation MPC to allow satellite operators to calculate collision probabilities conjunction analyses without sharing private information about the trajectories of their satellites. In this work, we report on the design and implementation of a new MPC framework for high-precision arithmetic on real-valued variables in a two-party setting where, unlike previous works, there is no honest majority, and where the players are not assumed to be semi-honest. We show how to apply this new solution in the domain of securely computing conjunction analyses. Our solution integrates the integer-based Goldreich-Micali-Wigderson GMW protocol and Garbled Circuits GC. We prove security of our protocol in the two party, semi-honest setting, assuming only the existence of one-way functions and Oblivious Transfer the OT-hybrid model. The protocol allows a pair of satellite operators to compute the probability that their satellites will collide without sharing their underlying private orbital information. Techniques developed in this paper would potentially have a wide impact on general secure numerical analysis computations. We also show how to strengthen our construction with standard arithmetic message-authentication-codes MACs to enforce honest behavior beyond the semi-honest setting. Computing a conjunction analysis requires numerically estimating a complex triple integral to a high degree of precision. The complexity of the calculation, and the possibility of numeric instability presents many challenges for MPC protocols which typically model calculations as simple integer arithmetic or binary circuits. Our secure numerical integration routines are extremely stable and efficient, and our secure conjunction analysis protocol takes only a few minutes to run on a commodity laptop. The full version appears ini?ź[HLOW16].

Assessing the Need for Supercomputing Resources Within the Pacific Area of Responsibility

Abstract : Located in Kihei on the island of Maui, Hawaii, the Maui High Performance Computing Center(MHPCC) was established in 1993 as a center within the Department of Defenses (DoD) High Performance Computing Modernization Program (HPCMP). As one of the five HPCMP centers, MHPCCs primary mission is to provide computing cycles and other high performance computing (HPC) capabilities to DoDs research, development, test and evaluation (RDT and E) community. DoD scientists and engineers from around the world utilize MHPCCs hardware, software, and technical talent to develop and support war-fighting capabilities. Currently, MHPCCs largest machine, Riptide, represents 3 percent of the total computing cycles across the HPCMP enterprise in support of this broader mission. MHPCC is managed by the Directed Energy Directorate within the Air Force Research Laboratory (AFRL), which oversees the sites annual operating budget of

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

14 million and supports about 50 personnel. In the fall 2014, Congress asked DoD to begin considering ways to cut about

Confronting Space Debris: Strategies and Warnings from Comparable Examples Including Deepwater Horizon

45 million from the HPCMP so future fiscal years could be supported entirely by the Armys programmed budget of

An Intelligence in Our Image: The Risks of Bias and Errors in Artificial Intelligence

183 million. Findings within this report are designed to provide AFRLdecision makers with important context about potential future missions and use cases for MHPCC as Congress, the Army, and the HPCMP work toward a solution for resolving the budget gap. To help provide AFRL with this context, we sought to answer the following research questions: Which of MHPCCs capabilities are used most often by customers in the Pacific area of responsibility (AOR), notably U.S. Pacific Command (PACOM)? And, specifically, is there a demand for a supercomputing resource that is located within the AOR? What recommendations should AFRL consider when making decisions about the future of MHPCC? We adopted a three-step approach to gather the data necessary to address these questions.