Secure, User-controlled Data

Most people with smartphones use a range of applications that collect personal information and store it on Internet-connected servers — and from their desktop or laptop computers, they connect to Web services that do the same. Some use still other Internet-connected devices, such as thermostats or fitness monitors, that also store personal data online.

Generally, users have no idea which data items their apps are collecting, where they’re stored, and whether they’re stored securely. Researchers at MIT and Harvard University hope to change that, with an application they’re calling Sieve.

With Sieve, a Web user would store all of his or her personal data, in encrypted form, on the cloud. Any app that wanted to use specific data items would send a request to the user and receive a secret key that decrypted only those items. If the user wanted to revoke the app’s access, Sieve would re-encrypt the data with a new key.

“This is a rethinking of the Web infrastructure,” says Frank Wang, a PhD student in electrical engineering and computer science and one of the system’s designers. “Maybe it’s better that one person manages all their data. There’s one type of security and not 10 types of security. We’re trying to present an alternative model that would be beneficial to both users and applications.”

The researchers are presenting Sieve at the USENIX Symposium on Networked Systems Design and Implementation this month. Wang is the first author, and he’s joined by MIT associate professors of electrical engineering and computer science Nickolai Zeldovich and Vinod Vaikuntanathan, who is MIT’s Steven and Renee Finn Career Development Professor, and by James Mickens, an associate professor of computer science at Harvard University.

Selective disclosure

Sieve required the researchers to develop practical versions of two cutting-edge cryptographic techniques called attribute-based encryption and key homomorphism.With attribute-based encryption, data items in a file are assigned different labels, or “attributes.” After encryption, secret keys can be generated that unlock only particular combinations of attributes: name and zip code but not street name, for instance, or zip code and date of birth but not name.

The problem with attribute-based encryption — and decryption — is that it’s slow. To get around that, the MIT and Harvard researchers envision that Sieve users would lump certain types of data together under a single attribute. For instance, a doctor might be interested in data from a patient’s fitness-tracking device but probably not in the details of a single afternoon’s run. The user might choose to group fitness data by month.

This introduces problems of its own, however. A fitness-tracking device probably wants to store data online as soon as the data is generated, rather than waiting until the end of the month for a bulk upload. But data uploaded to the cloud yesterday could end up in a very different physical location than data uploaded by the same device today.

So Sieve includes tables that track the locations at which grouped data items are stored in the cloud. Each of those tables is encrypted under a single attribute, but the data they point to are encrypted using standard — and more efficient — encryption algorithms. As a consequence, the size of the data item encrypted through attribute-based encryption — the table — is fixed, which makes decryption more efficient.

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