The Defence Advanced Research Projects Agency (DARPA), an investor in breakthrough technologies, looks set on its next great Cyber Grand Challenge of developing software that is able to spot and protect vulnerabilities in programmes before hackers are even aware they are there.
Due to the complexity of modern software, and given there is a need for quick fixes as more and more devices are connected to the internet become available, all of these devices will be used in vast quantities will not be able to have a sufficient defences against threats. This is the Cyber Grand Challenge that DARPA is taking on – to stop hackers in their tracks before vulnerabilities even come to light!
Automated Defence
A lot of anti-virus software already uses automated systems because of the huge level of malicious software that is out there. Its estimated that over 500 million Trojans, worms, and other viruses are circulating on the net, and more are being created and distributed every single day.
As traditional anti-virus software was poor at dealing with malware software it had not come across (typical anti-virus software can only protect about 30-40% of all the things that we need protected), a need for automated systems to help combat these threats was borne.
For the remaining percentage, security companies have used sophisticated, next-generation, software that can identify malicious codes it does not recognise. This was also combined with systems that would keep an eye on programmes and sound the alarm if something unexpected happened.
Other defence systems includes ‘setting off’ the malicious code in a virtual container in order to figure out what the malware was trying to do.
All very clever stuff!
Catching malicious threats
As malicious data continues to develop with new codes being created every day, technology has helped security software develop to be able to protect against 60% – 70% of data threats. The way in which software analyses malware is changing, and machine learning analyses the core make-up of the DNA, instead of only looking at each individual case. This is proving to be very useful.
Machine learning software can be implemented in order to protect all sorts of things that cyber criminals want to get access to, from home PCs, to government and company databases. Machine learning will mean software being able to spot things that humans would not notice which would offer much better protection.
The new smart software is not the solution to all the problems, however. There were instances where human intelligence was required to make the final decision about some of the things that the software would pick up.
As malware also develops further so that it can go unnoticed by developing software, the software needs to be developed to be able to keep up with ever developing malware.
It’s a long and arduous cycle!
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