No Data, No Problem—Giving Nuclear Inspectors Better Tools without Revealing State Secrets

Nuclear safeguards protect nuclear material from being diverted from legitimate activities, like nuclear power applications or nuclear physics research, to more sinister purposes. International regulations dictate the safeguards protocols that must be adhered to, and in general, nations meet these obligations as necessary. However, reluctance on the part of participating nations and their businesses to yield more information than is absolutely necessary stands as an obstacle against bringing the full force of modern data analytics to bear in safeguards applications. Privacy-preserving computation, including secure multiparty computation (MPC), presents a solution. Garbled circuits, a specific class of MPC algorithms, allow multiple parties (in this case an international inspector and a nation-state or nuclear facility) to jointly perform calculations without revealing their respective inputs. Having previously shown that garbled circuits can successfully identify anomalies in time series data, this work pivots to showing that these anomaly detection circuits can distinguish anomalous events in categorically specific nuclear safeguards relevant time series.