DARPA takes step toward 'holy grail of encryption'

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The U.S. defense department is searching for what could be considered the "holy grail of data encryption," which would seal up a loophole that allows hackers to access sensitive information while it's being processed.

In modern encryption, a well-defined set of calculations, known as an algorithm, scrambles data so that it's no longer readable. Those allowed access to the data are given a string of numbers called a key, which is the code that lets you unscramble that data again.

If someone wanted to use the encrypted data to do anything useful, they first would have to decrypt it back into so-called "plain text," which makes it susceptible to snooping again. To help protect that now decrypted information, those working with the plain text typically only do soon trusted computers. But, as is apparent from regular headlines about data breaches at major organizations, it's becoming difficult to tell which devices are secure.

That's why DARPA is trying to spur breakthroughs in something called fully homomorphic encryption (FHE). The technique makes it possible to analyze compute data while it's still in encrypted form. That could allow financial crimes investigators to scour sensitive bank records without exposing customer details, for instance, or let health researchers analyze private health data while preserving patients' privacy, Rondeau said. The technique could also help the military keep their battlefield data more secure and make it easier to let allies work with classified intelligence data.

The key to the approach is in its name, which is derived from the Greek words "homos," meaning "same," and "morphe," meaning "shape." It refers to the fact that certain mathematical operations can map data from one form to another without altering the underlying structure of the data. That means changes made to the data while in one form will be preserved when that data is converted back to the other. This principle can be applied to encryption, because computers represent all data, including text, as numbers.

So rather than describing each data point's position with simple X, Y coordinates, the number of axes can be huge, with each unique piece of data being described by thousands of coordinates. Data points can also be positioned between dots, so each coordinate can have many decimal places to denote their precise location. This makes the encryption essentially impossible to crack, even by quantum computers. That's a promising feature, Rondeau said, because today's leading encryption methods are not quantum-proof.

The big problem is that processing this data is very slow on current computers — roughly a million times slower than processing times for unencrypted data. That's why DARPA has launched a research program called Data Protection in Virtual Environments (DPRIVE), which Rondeau is managing, to speed things up. The program recently awarded contracts to an encryption start-up Duality Technologies, software company Galois, nonprofit SRI International and a division of Intel, called Intel Federal to design new processors and software to boost speeds to just 10 times slower than normal, which is 100,000 times faster than current processing for fully homomorphic encryption.

FHE is so slow because of the way computations are carried out.To complicate matters more, those data points don't remain static. Researchers discovered you can carry out mathematical operations such as multiplication or addition by moving data points around inside the lattice. By combining lots of these operations, researchers can carry out all kinds of computations without decrypting the data. When you decode the answer, there's a chance that someone could spy on it; but that answer still wouldn't reveal anything about the data used to compute it.

There are two main approaches the DARPA-funded companies can use to simplify things, Rondeau said. One tactic is to improve the computer's ability to deal with high-precision numbers, by changing the way numbers are represented in binary code and altering chips circuits to process them more efficiently. The other is to translate the data into a lower dimensional space where the calculations are simpler, which also requires new hardware and software approaches.

Edd Gent is a British freelance science writer now living in India. His main interests are the wackier fringes of computer science, engineering, bioscience and science policy. Edd has a Bachelor of Arts degree in Politics and International Relations and is an NCTJ qualified senior reporter. In his spare time he likes to go rock climbing and explore his newly adopted home.