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COMPUTING SCIENCE

Alice and Bob in Cipherspace

A new form of encryption allows you to compute with data you cannot read

Brian Hayes

Putting Code to Work

Lauter, Naehrig and Vaikuntanathan also discuss some of the ways we might use homomorphic computing. Ensuring the privacy of online medical records is one application. The patient would grant doctors access to selected records by sharing a secret key.

Wall Street is another potential customer for homomorphic services. The “quants” who base investment decisions on computational analysis have a strong proprietary interest not only in their data but also in their algorithms. With FHE both can be protected by the same mechanism.

A third idea is to build a cryptographic privacy fence between online advertisers and consumers. Advertisers, eager to reach individuals with specific interests or habits, gather and cross-index data on people’s activities on the Internet and elsewhere. A service based on homomorphic encryption could match ads to targeted consumers while ensuring that advertisers learn nothing about the people selected.

When I asked Vaikuntanathan what application he thought might be deployed first, he had another suggestion: spam filtering. If you publish a public key and invite correspondents to send you encrypted email, a spammer can take advantage of the key to encrypt advertisements and the other effluvia that fills our mailboxes. Spam-filtering services cannot read and reject the encrypted spam unless you are willing to share your decryption key; homomorphic encryption could solve that problem.

My own fantasy application is an offshore bank called the Homomorphic Trust Company. The online interface might look much the same as any other bank’s, with the usual cryptographic safeguards against intruders. But at this bank, even the bankers could not know the details of your transactions. I think Alice might be interested; she could get rid of that suitcase full of uncountable cash.

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