AI And Cybersecurity - Do Humans NEED To Be Made Obsolete? Articles Chief Innovation Officer

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This is significant when you consider the importance of time when it comes to hacks. Once a business has been infiltrated, the length of time it takes to detect the intrusion has a momentous influence on how much damage is done and how easily the threat can be neutralized. 'The median time for detection is one hour. High-performance companies typically do this is in under 10 minutes - but low performing companies take days or weeks' according to Johanna Till Johnson, CEO at Nemertes Research.For example, when ransomware like the one which affected the NHS, penetrates a business, that is only the first step in the damage it causes. Once it's in, it starts encrypting all the data in that system, which can take time, so it needs to evade detection until it has finished.


Why AI could be the key to turning the tide in the fight against cybercrime

ZDNet

A specially programmed AI can'think' about cybersecurity in a more complex detail than a human can. It's not unreasonable to suggest the cybersecurity battle is being lost - and on more than one front. Not only are more efficient and organised cybercriminals winning the security arms race against their corporate targets, there's also a shortage of cybersecurity professionals equipped with the skills required to fight hackers. Some claim the fight against online crooks will be bolstered not by hiring more people but rather by machines using techniques based around artificial intelligence, machine learning, and deep learning. This doesn't mean self-learning machines will be outright replacing cybersecurity professionals, however, but rather augmenting what they're able to do and taking care of the most basic tasks.


Why AI could be the key to turning the tide in the fight against cybercrime ZDNet

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A specially programmed AI can'think' about cybersecurity in a more complex detail than a human can. It's not unreasonable to suggest the cybersecurity battle is being lost - and on more than one front. Not only are more efficient and organised cybercriminals winning the security arms race against their corporate targets, there's also a shortage of cybersecurity professionals equipped with the skills required to fight hackers. Some claim the fight against online crooks will be bolstered not by hiring more people but rather by machines using techniques based around artificial intelligence, machine learning, and deep learning. This doesn't mean self-learning machines will be outright replacing cybersecurity professionals, however, but rather augmenting what they're able to do and taking care of the most basic tasks.


Why AI-based threat detection hasn't taken over the market … yet

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According to Nicole Eagan, CEO of software company Darktrace, only two out of every ten cybersecurity experts typically embrace artificial intelligence (AI) as a key component of threat detection. The others, she explains, tend to be "totally resistant" or agree to "give [AI] a try" but don't put in the effort required to make the most of the tech post-purchase. Granted, information security professionals are known to be risk-averse, which has the flip side of sometimes making them resistant to try out new tech -- and for good reason: Protecting the company against risk is the number one job. Yet, theoretically, AI has the potential to more quickly identify a larger number of problems. Mike Small, senior analyst for research firm KuppingerCole, believes many actually do -- they just might not think of it as AI.


How machine learning can be used to catch a hacker

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The tools that hackers use today are sophisticated, which makes them hard to track down after an attack. TechRepublic's Dan Patterson met with SecBI's Alex Vaystikh and Gilad Peleg to discuss how artificial intelligence (AI) can enhance threat detection systems.