Supercomputers have become essential for National Security, for decoding encrypted messages, simulating complex ballistics models, nuclear weapon detonations and other WMD, developing new kinds of stealth technology, and cyber defence/ attack simulation. Because of the expense, supercomputers are typically used for the most intensive calculations, like predicting climate change, or modeling airflow around new aircraft.
Identifying cybersecurity threats from raw internet data can be like locating a needle in a haystack. The amount of internet traffic data generated in a 48-hour period, for example, is too massive for one or even 100 laptops to process into something digestible for human analysts.
Oak Ridge National Lab’s Summit supercomputer can process more than 122 petaflops – that’s 122 thousand trillion floating point operations per second. China’s Sunway TaihuLight, which held the top spot for the past five years, can do 93.
They are also essential for Cybersecurity, “Being able to process network data in real near time to see where threats are coming from, to see what kinds of connections are being made by malicious nodes on the network, to see the spread of software or malware on those networks, and being able to model and interdict and track the dynamics on the network regarding things that national security agencies are interested in,” Tim Stevens, a teaching fellow in the war studies department at King’s College London says, “those are the realms in which supercomputing has a real future.”
One advantage that supercomputers offer over traditional approaches is that a supercomputer can look at a large volume of data all at once. “It can find those nuanced relationships across systems, across users, across geolocations, that could indicate early warning of a potential breach,” said Anthony Di Bello, senior director of security, discovery, and analytics at OpenText.
Officials at DARPA, the U.S. defense agency sponsored a contest in 2016 where Giant refrigerator-sized supercomputers battled each other in a virtual contest to show that machines can find software vulnerabilities, giving possible glimpse of the future of cybersecurity. The result: the supercomputers time and time again detected simulated flaws in software.
It represents a technological achievement in vulnerability detection, at a time when it can take human researchers on an average a year to find software flaws. The hope is that computers can do a better job and perhaps detect and patch the flaws within months, weeks or even days.
A global enterprise with 200,000 machines could be processing petabytes of data every day, he said. “I’m looking for a needle in a haystack of needs. I need faster computing.” That’s why analysts rely on sampling to search for potential threats, selecting small segments of data to look at in depth, hoping to find suspicious behavior. While this type of sampling may work for some tasks, such as identifying popular IP addresses, it is inadequate for finding subtler threatening trends.
“If you’re trying to detect anomalous behavior, by definition that behavior is rare and unlikely,” says Vijay Gadepally, a senior staff member at the Lincoln Laboratory Supercomputing Center (LLSC). “If you’re sampling, it makes an already rare thing nearly impossible to find.”
It could be at least two or three years before we start seeing real-world uses of supercomputers for cybersecurity, he said. “The big tech giants are more focused on other use cases at this point
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