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Random generator: The digital circuits at the center of this electron micrograph image can emit a stream of random numbers at high speed. Such circuits could be integrated into future processors.
Intel
Intel unveils a circuit that can pump out truly random numbers at high speed.
It might sound like the last thing you need in a precise piece of hardware, but engineers at Intel are pretty pleased to have found a way to build a circuit capable of random behavior into computer processors.
Generating randomness--an unpredictable stream of numbers--is much harder than you might think. It's also crucial to creating the secure cryptographic keys needed to keep data safe. Building a random-number-generating ability into the Central Processing Unit (CPU) at a computer's heart is ideal, says Ram Krishnamurthy, an engineer at Intel's Microprocessor Technology Labs, in Hillsboro, OR. It should speed up any process that requires the generation of an encrypted key, for example securing sensitive data on a hard drive, and make it harder for an attacker to compromise that encryption.
Building circuitry capable of producing random numbers into a CPU has proved difficult. "Today random numbers are either generated in software, or in the chip set outside the microprocessor," explains Krishnamurthy, one of the Intel researchers on the project.
Neither solution is ideal. Software produces only pseudo random numbers (given enough computing power, patterns can be found within that randomness).
"If the random numbers are not truly random, for example, if they are biased in some way, then an adversary has a better chance of guessing/determining the value," explains mathematician Elaine Barker, at the National Institute for Standards and Technology (NIST), in Gaithersburg, MD. "In the case of cryptographic keys, if the adversary can determine the key without an excessive amount of computing power, then he can breach the confidentiality of that data."
Installing a source of random numbers outside of a computer's core microprocessor provides another avenue of opportunity to attackers, says Krishnamurthy. "You are vulnerable to side channel attacks," he explains, "there are many ways by which the key can be directly read off of the bus, or attacks that look at how the power supply varies and look for signatures that indicate what the key looks like."
Building the circuit into the main processor shuts off that possibility, says Krishnamurthy, although the barrier to doing that has been practicality. The best-established methods of generating random numbers use analog circuits that rely on thermal noise as a source of randomness, and those circuits are not easily fabricated with the techniques used to make the digital circuits of a microprocessor. Nor are they easily scaled down to the size of components on modern chips.
Intel's new circuit has a fully-digital design, making it possible to incorporate it into the microprocessor die. At the heart of the new design is a cross-coupled inverter, a combination of two basic circuit components that is essentially a memory capable of storing a single 1 or 0. This memory, though, is designed to be unreliable; it can be tipped between its two possible outputs by the influence of thermal noise from the surrounding silicon. Since that thermal noise is random, the circuit's output should be, too.
In reality, though, the influence of fluctuations in voltage and temperature normal inside a chip could bias that output to be less-than-random, requiring Krishnamurthy and colleagues to develop additional measures to counteract their influence. Benchmarks for "true" randomness maintained by NIST were used to confirm they had been successful. "We exceeded all of those thresholds," he says. The speed at which the new circuit cranks out numbers--2.4 billion a second or 2.4Gbps--is also around 200 times faster than anything before, Krishnamurthy adds.
Having built the circuit with a smallest feature size of 45 nanometers, he and colleagues are now working toward proving it can be built using 32 and 22 nanometer manufacturing processes with minimal design tweaks.
Passing existing benchmarks of randomness, though, does not mean the new circuit is perfect. Current techniques do not make it possible to be certain that any source of randomness is truly random, says Barker. "We just don't know enough to design tests that catch all the problems, and tests may not always catch the point at which a noise source starts to go bad if the change is subtle." Research by groups like that at NIST will generate smarter tests that help industry engineers raise the bar further.
If you can test for it, it can not be random
I have had a long standing problem with the whole process of quinafying randomness. A lack of a patteren is in it self a patteren. To crack a sequance that has been certivied random, all that you would need is a starting point, and a knolage of the patteran seeking system that is used for determination of randomness. Affter you throw out any sequance that fits any of your test. What you are left with is a reproduction of your random sequance, using purely anlyical methodes. Conclusion: since any sequance of numbers that can be produced anliticly can not be random by defination. There for: The very abbilaty to test for randomness vilates the resalt of the test by creating a method by wich the sequance of "random numbers" can be perdicted.
I will leave the first part of this post because it is a relavent question on perdictabilty, and showes how easy it is to fall into the trap of equating random and unperdictable.
So here is my question for brains bigger then mine. Given that as i understand it the deffinotion of a random sequance of numbers ware the next number in the sequance dose not follow from the proceding numbers. Ware i see a problem is that i have always understode "follow" to mean "not determined by" Ie given any subset of numbers of any size, that the ocurance of said subset dose not determain the value of any of the following numbers. You may notice as i have that this dose not perclude that the appearance of the given subset perdicting the apperance of certan numbers in the available sequance only that random chance greated such perdictability in this picticular sequance. In fact a one in a billion ocurance showing up one billion times in a row should be just as likley as any other ocurance.
In conclusion any use of probability on random numbers can not be valid because all events must be equaly likley.
This naturaly leades to another false assumbtion that has been used to defraud companies out of billions. That since all things are equaly probable then the disterbiutaion of events must be even given a long enough random sequance. This is easely dispeled by the realization that all things being equaly probable includes an uneaven disterbiutaion.
Hope some can help me with this, because the only concluesion i can draw from this is that randomness can not be proved or disproved by looking at the generated number sequance because all posiable sequances are posibale if the generator of the numbers is truly a random event.
to get back to IBM's chip the numbers may appear random, but they are produced by the application of well understod physical laws and thear by do indeed follow, from one to the next in a none random sequance. Not withstanding that their is no posiable way to optain enough information about the enviorment suronding the chip to perdict the output. Thus they have greated a device ware the next number in the sequance is unknowable not random.
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ms
190 Comments
Bethesda?
Isn't NIST in Gaithersburg?
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tim.maher
3 Comments
Re: Bethesda?
You're right. Thanks for pointing that out. It's been fixed in the article.
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