Ad Hoc Multi-Input Functional Encryption
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Ad Hoc Multi-Input Functional Encryption

Authors Shweta Agrawal, Michael Clear, Ophir Frieder, Sanjam Garg, Adam O'Neill, Justin Thaler

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Author Details

Shweta Agrawal
  • Dept. of Computer Science and Engineering, IIT Madras, Chennai, India
Michael Clear
  • Dept. of Computer Science, Georgetown University, Washington, DC, USA
Ophir Frieder
  • Dept. of Computer Science, Georgetown University, Washington, DC, USA
Sanjam Garg
  • Dept. of EECS, University of California at Berkeley, CA, USA
Adam O'Neill
  • Dept. of Computer Science, University of Massachusetts, Amherst, MA, USA
Justin Thaler
  • Dept. of Computer Science, Georgetown University, Washington, DC, USA

Funding

  • Garg, Sanjam: Research supported in part from DARPA/ARL SAFEWARE Award W911NF15C0210, AFOSR Award FA9550- 15-1-0274, AFOSR YIP Award, DARPA and SPAWAR under contract N66001-15-C-4065, a Hellman Award and research grants by the Okawa Foundation, Visa Inc., and Center for Long-Term Cybersecurity (CLTC, UC Berkeley). The views expressed are those of the author and do not reflect the official policy or position of the funding agencies.

Acknowledgements

We thank Romain Gay for pointing out a subtlety in the security definition of (standard) MIFE for inner products, which necessitated a minor adjustment in our ad hoc MIFE construction.

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Shweta Agrawal, Michael Clear, Ophir Frieder, Sanjam Garg, Adam O'Neill, and Justin Thaler. Ad Hoc Multi-Input Functional Encryption. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 40:1-40:41, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.ITCS.2020.40

Abstract

Consider sources that supply sensitive data to an aggregator. Standard encryption only hides the data from eavesdroppers, but using specialized encryption one can hope to hide the data (to the extent possible) from the aggregator itself. For flexibility and security, we envision schemes that allow sources to supply encrypted data, such that at any point a dynamically-chosen subset of sources can allow an agreed-upon joint function of their data to be computed by the aggregator. A primitive called multi-input functional encryption (MIFE), due to Goldwasser et al. (EUROCRYPT 2014), comes close, but has two main limitations: 
- it requires trust in a third party, who is able to decrypt all the data, and 
- it requires function arity to be fixed at setup time and to be equal to the number of parties. 
To drop these limitations, we introduce a new notion of ad hoc MIFE. In our setting, each source generates its own public key and issues individual, function-specific secret keys to an aggregator. For successful decryption, an aggregator must obtain a separate key from each source whose ciphertext is being computed upon. The aggregator could obtain multiple such secret-keys from a user corresponding to functions of varying arity. For this primitive, we obtain the following results: 
- We show that standard MIFE for general functions can be bootstrapped to ad hoc MIFE for free, i.e. without making any additional assumption. 
- We provide a direct construction of ad hoc MIFE for the inner product functionality based on the Learning with Errors (LWE) assumption. This yields the first construction of this natural primitive based on a standard assumption. 
 At a technical level, our results are obtained by combining standard MIFE schemes and two-round secure multiparty computation (MPC) protocols in novel ways highlighting an interesting interplay between MIFE and two-round MPC.

Subject Classification

ACM Subject Classification
  • Security and privacy → Cryptography
  • Security and privacy → Public key (asymmetric) techniques
  • Security and privacy → Mathematical foundations of cryptography
Keywords
  • Multi-Input Functional Encryption

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