Table 1.

Glossary of topics for iDASH competitions

#	Topic	Description and references
1	Privacy-preserving data sharing	Allow differentially private federated data analysis with fragmented data from distributed sources21
2	Secure release	Support differentially private data release with mitigated risks of information leakage22
3	Secure outsourcing	Delegate data storage and analysis on untrusted third party servers23,24
4	Homomorphic encryption	Support encrypted operations to match the plaintext operation with advanced cryptographic techniques, without leaking information25,26
5	Secure collaboration	Collaboration among two or more parties to perform a computation jointly, without sharing their own raw data27
6	Secure multiparty computation	Cryptographic techniques to perform computation jointly by two or more parties on encrypted data28
7	Beacon service	Evaluation of a human genomic data sharing service developed by the GA4GH to check whether a human genomic dataset contains a genome with a specific variant (nucleotide) at a specific chromosomal location29
8	Privacy-preserving search	Support for the calculation of distances between two genome sequences, without revealing variants30
9	Encryption testing	Allowing genetic testing on encrypted data and results that can only be decrypted by data owners who have the secret key
10	Deduplication	Removal of duplicate records in a database31
11	Software guard extensions	Application of isolation techniques developed by Intel hardware to protect data in use32
12	Secure search	Identification of a query record in an encrypted database33
13	Blockchain and smart contract	Distributed ledger technology that allows both decentralized sharing of data (blockchain34–36) and code (smart contracts37–39)
14	Secure machine learning	Building of machine learning models from encrypted data40–42
15	Privacy-preserving machine learning	Execution of plaintext models on encrypted data to preserve data privacy43–47

iDASH: integrating data for analysis, anonymization and sharing.