Introduction to AI-based threat prevention
The shifting security landscape presents challenges to those working in the area of threat detection and prevention. The expansion of endpoints created by hyper-connected IT infrastructures, the Internet of Things (IoT) and mobile computing offers cybercriminals a myriad of doorways into our networks. And as the technology matrix morphs into something from a sci-fi film, cybercriminals are creating clever and stealthy tools like fileless malware.
This would be bad enough, but the cybersecurity skills gap is exacerbating the situation. Security analysts are on the front line of security and they are feeling the pressure of this complex problem. But with a shortfall of 1.8 million cybersecurity professionals by 2022 according to (ISC)2, this pressure looks only set to get worse.
In a study titled “The 2018 Threat Hunting Report,” 52% of Security Operations Centers (SOC) said that threats had at least doubled in the last year. The same study also found that 82% of SOCs would be investing in the use of ‘advanced’ threat hunting techniques like artificial intelligence (AI).
This article will look at how AI is applied in the area of threat detection and prevention, and who is using it.
Use of artificial intelligence in threat detection and prevention
The type of threats and the scope of attack vectors has made the detection and prevention of cyberattacks very difficult. To counterbalance the onslaught, we have to get smart.
Smart security has now turned up in the form of artificial intelligence. AI is held up as a new technology that offers a way to automate the detection process — augmenting, rather than replacing, the human analyst. The market for AI-based solutions in the security space is expected to reach $34.8 billion by 2025 as new technologies and threats (Read more...)
*** This is a Security Bloggers Network syndicated blog from Infosec Resources authored by Susan Morrow. Read the original post at: http://feedproxy.google.com/~r/infosecResources/~3/GGmpMdg1t6Y/