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Black Block Recorder: Immutable Black Box Logging for Robots via Blockchain

Ruffin White, Gianluca Caiazza, Agostino Cortesi, Young Im Cho, Henrik I. Christensen

Year
2019
Citations
26

Abstract

Event data recording is crucial in robotics research, providing prolonged insights into a robot's situational understanding, progression of behavioral state, and resulting outcomes. Such recordings are invaluable when debugging complex robotic applications or profiling experiments ex post facto. As robotic developments mature into production, both the roles and requirements of event logging will broaden, to include serving as evidence for auditors and regulators investigating accidents or fraud. Given the growing number of high profile public incidents involving self-driving automotives resulting in fatality and regulatory policy making, it is paramount that the integrity, authenticity and non-repudiation of such event logs are maintained to ensure accountability. Being mobile cyber-physical systems, robots present new threats, and vulnerabilities beyond traditional IT: unsupervised physical system access or postmortem collusion between robot and OEM could result in the truncation or alteration of prior records. In this letter, we address immutablization of log records via integrity proofs and distributed ledgers with special considerations for mobile and public service robot deployments.

Keywords

RobotComputer scienceComputer securityBlockchainDebuggingProfiling (computer programming)Artificial intelligenceOperating system

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