Privacy-preserving scoring of tree ensembles : a novel framework for AI in healthcare

Machine Learning (ML) techniques now impact a wide variety of domains. Highly regulated industries such as healthcare and finance have stringent compliance and data governance policies around data sharing. Advances in secure multiparty computation (SMC) for privacy-preserving machine learning (PPML) can help transform these regulated industries by allowing ML computations over encrypted data with personally identifiable information (PII). Yet very little of SMC-based PPML has been put into practice so far. In this paper we present the very first framework for privacy-preserving classification of tree ensembles with application in healthcare. We first describe the underlying cryptographic protocols that enable a healthcare organization to send encrypted data securely to a ML scoring service and obtain encrypted class labels without the scoring service actually seeing that input in the clear. We then describe the deployment challenges we solved to integrate these protocols in a cloud based scalable risk-prediction platform with multiple ML models for healthcare AI. Included are system internals, and evaluations of our deployment for supporting physicians to drive better clinical outcomes in an accurate, scalable, and provably secure manner. To the best of our knowledge, this is the first such applied framework with SMC-based privacy-preserving machine learning for healthcare

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control

Space Station Freedom data management system growth and evolution report

The Information Sciences Division at the NASA Ames Research Center has completed a 6-month study of portions of the Space Station Freedom Data Management System (DMS). This study looked at the present capabilities and future growth potential of the DMS, and the results are documented in this report. Issues have been raised that were discussed with the appropriate Johnson Space Center (JSC) management and Work Package-2 contractor organizations. Areas requiring additional study have been identified and suggestions for long-term upgrades have been proposed. This activity has allowed the Ames personnel to develop a rapport with the JSC civil service and contractor teams that does permit an independent check and balance technique for the DMS

Improved IEEE 802.11 point coordination function considering fiber-delay difference in distributed antenna systems

In this paper, we present an improved IEEE 802.11 wireless local-area network (WLAN) medium access control (MAC) mechanism for simulcast radio-over-fiber-based distributed antenna systems where multiple remote antenna units (RAUs) are connected to one access point (AP). In the improved mechanism, the fiber delay between RAUs and central unit is taken into account in a modification to the conventional point coordination function (PCF) that achieves coordination by a centralized algorithm. Simulation results show that the improved PCF outperforms the distributed coordination function (DCF) in both the basic-access and request/clear-to-send modes in terms of the total throughput and the fairness among RAU

Advanced manned space flight simulation and training: An investigation of simulation host computer system concepts

The findings of a preliminary investigation by Southwest Research Institute (SwRI) in simulation host computer concepts is presented. It is designed to aid NASA in evaluating simulation technologies for use in spaceflight training. The focus of the investigation is on the next generation of space simulation systems that will be utilized in training personnel for Space Station Freedom operations. SwRI concludes that NASA should pursue a distributed simulation host computer system architecture for the Space Station Training Facility (SSTF) rather than a centralized mainframe based arrangement. A distributed system offers many advantages and is seen by SwRI as the only architecture that will allow NASA to achieve established functional goals and operational objectives over the life of the Space Station Freedom program. Several distributed, parallel computing systems are available today that offer real-time capabilities for time critical, man-in-the-loop simulation. These systems are flexible in terms of connectivity and configurability, and are easily scaled to meet increasing demands for more computing power

Graceful Termination -- Graceful Resetting

Correct — let alone graceful — termination of parallel systems is sometimes thought to be a difficult problem. This is particularly imagined to be so under the pure message-passing MIMD discipline of occam and transputer networks, where global operations (like setting a shared flag or abortions) are not allowed and where time-outs cannot be set for every communication. This paper describes some common, but erroneous, occam approaches to this problem and contrasts them with what can be done in Ada [0, 1, 2]. These methods are all rejected on the grounds of insecurity and performance overheads. A simple, legal, secure and efficient occam method is then presented. This method also solves a much more important problem — the general (or partial) resetting of a parallel system (or sub-system). The resetting mechanism is quite independent of the parallel application algorithm, which can therefore be developed without worrying about such matters. This separation of concerns is good software engineering and is fully supported by the occam philosophy. Finally, an application of this resetting mechanism is described that permits the dynamic reconstruction of occam network topologies