Safe and secure practical autonomy

Safe practical autonomy is ensured by encapsulating an unreliable or untrusted machine learning algorithm within a control-based algorithm. A safety envelope is utilized to ensure that the machine learning algorithm does not output control signals that are beyond safe thresholds or limits. Secure pr...

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Bibliographic Details
Main Authors Wolford, Brian R, McLean, Angus L, Roup, Alexander V, Bertram, Joshua R
Format Patent
LanguageEnglish
Published 19.05.2020
Subjects
AEROPLANES
AIRCRAFT
ANALOGUE COMPUTERS
AVIATION
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROLLING
COSMONAUTICS
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
GYROSCOPIC INSTRUMENTS
HELICOPTERS
MEASURING
MEASURING DISTANCES, LEVELS OR BEARINGS
NAVIGATION
PERFORMING OPERATIONS
PHOTOGRAMMETRY OR VIDEOGRAMMETRY
PHYSICS
REGULATING
SIGNALLING
SURVEYING
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
TESTING
TRAFFIC CONTROL SYSTEMS
TRANSPORTING
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Summary:Safe practical autonomy is ensured by encapsulating an unreliable or untrusted machine learning algorithm within a control-based algorithm. A safety envelope is utilized to ensure that the machine learning algorithm does not output control signals that are beyond safe thresholds or limits. Secure practical autonomy is ensured by verification using digital certificates or cryptographic signatures. The verification may be for individual partitions of an autonomous system or apparatus. The partitions include trusted and untrusted partitions. Trusted partitions are verified for security, while untrusted partitions are verified for safety and security.
Bibliography:Application Number: US201715629548