FEATURE
cybersecurityeurope
CHARTS
Called Frontier, it has achieved
1.102 exafl ops during a benchmarking exercise and has been called the world’s fastest computer. At the Massachusetts Institute of
Technology’s Lincoln Laboratory Supercomputing Cente algorithms have been in development that look for anomalies in data fl ows to detect cyberattacks. Super computers are needed because the datasets are enormous. Just 15 minutes of raw internet traffi c data equates to about 20GB. Even with super computing the raw internet traffi c data needs to be divided up into 10 second batches, each of which can be examined for anomalies in a reasonable timeframe. Exascale computers would be able to examine longer durations of raw internet traffi c data making this surveillance tool more practical. The need for speed can now be demonstrated with the scale of events that just one corporate security centre monitors, Italian high technology company Leonardo’s Global Security Operation Centre, for example. It has monitored 115,000 security events every second, with 500,000 billion transactions processed for cyber intelligence purposes. A new approach to overseeing this huge
number of transactions is a greater focus on data management. Data cannot be left on the web without adequate protection for too long, hence the importance of the Lincoln Laboratory’s work. The machine learning that exascale computing can realise means automated processes for cyberattack detection. All of that unstructured internet raw traffi c needs to be structured
for analysis and artifi cial intelligence (AI) and the supercomputing it represents is the key. Reducing the time it takes to respond to attacks will be a key advantage. With exascale AI, adaptive networks will be
President Joe Biden also announced more support for cyber security to defend against the next generation of faster supercomputers
possible where reconfi guring, tracking, and adapting data fl ows to changing requirements will make for better security. Analytics and intelligence, control and automation means there can be real-time information about network effi ciency and vulnerabilities, allowing agencies to address them. Models of normal background network traffi c with real time analysis means unusual activity can be more readily detected with everything that means for the internet. That threat detection, whether it is across the internet or just a wide area network is going to need to be a part of every product and its security in an Internet of Things (IoT) world. There is the prospect of billions of IoT connected devices being trojan horses for malware. Each one potentially the origin of a denial of service attack, for example. It means supercomputing is going to be needed to identify and neutralise, in a reasonable timeframe, these potentially dumb hosts whose owners will not be aware they have been hijacked for nefarious purposes. The importance of machine intelligence and the supercomputing that underpins it was underlined by the United Kingdom’s AI
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