Intelligent CISO Issue 37 | Page 38

AI shows no signs of slowing down ; it is effective and addictive , which is why we have adopted it with open arms .
FEATURE
endpoints than they can realistically monitor or manage , owing to various reasons ranging from lack of qualified staff to expensive security programmes or policies .
While estimates vary , it ’ s well established that organisations are struggling to find and retain the talent needed to defend themselves . The skills gap is getting wider as organisations adopt more complex technologies and expand the threat surface . Security will always be an arms race between attackers and defenders . That said , AI is a potent tool because it allows us to create software that does a malware analyst ’ s job .
It takes many human years of experience and training to develop the skills and intuition to sniff out malware . Now we can train a program to do the same thing in just a few hours with AI learning algorithms and a huge amount of data . To be fair , there ’ s nothing better than a human analyst , but the gap is closing all the time and AI models only take seconds to analyse a file where a human analyst could take hours or days .
Thus , cybersecurity provides an excellent forum for applying AI . Well-trained and constantly learning models are far more predictive and effective than humans or legacy methods , such as individual signatures or heuristic rules that require updates multiple times per day .
Securing the endpoint with AI and ML
As you might expect , the cybersecurity industry benefits greatly from AI as we are using it for everything – from detecting threats to unusual network activity .
As quickly as technology evolves in this dynamic marketplace , organisations can adopt innovations before their network security can maintain data integrity . With companies rapidly integrating such connected technologies as IoT and countless cloud-based platforms designed to infuse significant efficiencies across their operations , network security can often lag behind those advanced systems . The result , of course , is networks filled with security gaps just waiting to be exploited . Additionally , when it comes to nextgeneration cybersecurity , traditional on-premises signature database protection models are ineffective and lack administrator visibility .
Most traditional and next-gen approaches rely on scanning files to detect attacks , making them extremely vulnerable to new attack techniques .
However , with an AI-based system tasked with the sole responsibility of constantly monitoring a company ’ s

AI shows no signs of slowing down ; it is effective and addictive , which is why we have adopted it with open arms .

38 www . intelligentciso . com