A new method for computer-generating random numbers is being called”remarkable”, and could help improve computer security.

Random numbers are important for computer encryption, lotteries, scientificmodelling, and gambling.

Current methods of generating random numbers can produce predictable results.

Researchers said the new method could generate higher-quality random numberswith less computer processing.

The problem of generating random numbers lies in the fact that computers arefundamentally predictable machines, running calculations and delivering answersbased on mathematics.

Slow and predictable

There are currently two main methods for generating random numbers.

In the first, a computer picks numbers according to an algorithm or from a pre-generated list.

This method, while fast and not requiring much computer power, is not trulyrandom, because the results are predictable.

The second method introduces an unpredictable element from the real world intothe algorithm.

This might be a reading of air temperature, a measurement of backgroundradiation, or variations in atmospheric noise.

Some of these measurements, however, have their own patterns – and may not betruly random.

They can also be difficult to acquire.

The new solution takes two “weak” random sources to generate a single, high-quality random number.

That made it a faster, more practical solution for an almost-perfectly randomnumber, said Prof Alan Woodward, of Surrey University, and it could haveimplications for encryption and security.

“In cryptography, random numbers are essential,” he said.

“Given enough time, all algorithms can be reverse-engineered.

“You have to build the algorithm so that it takes so long to reverse-engineer it’s notworth it.

“Random number equations are central to injecting this randomness.”

“It’s not often that cryptographers and mathematicians get excited… but it does looklike party time.

“It’s remarkable.”

Cornerstone of security

Dr Mads Haahr of Trinity College Dublin, who created the online random numbergenerator random.org, said the development was an improvement in efficiency, butnot a fundamental leap forward.

“While the paper might be a good contribution in the specific research area ofrandomness extraction, I would not call it a breakthrough… all those things arealready possible with existing methods and have been for many years,” he said.

“If the authors’ claims hold up, we will be able to do these things faster than before,and with equipment of poorer quality, which is great, but the method doesn’t enableany applications that weren’t possible before.

“I’m glad to see there is good research going on to improve the state of the art.

“In many ways, randomness is the under-appreciated cornerstone of data security.

“As regular users of information technology, we tend not to appreciate howimportant it is.”

The new method was detailed in a paper by two researchers from the University ofTexas, published online in July 2015.

It has taken almost a year for other researchers to examine its findings, expandupon the method, and for the original authors to add revisions.

The team will now present its research at the annual Symposium on Theory ofComputing in June, where it will be one of three recipients of the best paper award.