In 2021 weekly cyber-attacks on corporate networks went up 50% compared to 2020 according to Check Point Research. That means over 900 attacks per organization per week in the fourth quarter of 2021. What does this translate to?
Cyber Security is not a human-scale problem anymore. AI is and will be relied upon to handle this vast number of threats.
The first task of AI and ML when it comes to Cyber Security is identifying and prioritizing Zero-Day malware threats.
Trend Micro found that in 2021, 51% of IT security teams feel overwhelmed by attacks, and 55% state that they are not entirely capable of prioritizing and responding to them. To add to that, Trend Micro found that 27% of a team’s time is spent dealing with false positives, further taking up time and resources.
Apart from the high volume of threats, the sheer speed at which these threats adapt and change is a key issue for Cyber Security professionals. Malware keeps improving, and humans are unable to cope with the pressure. Even legacy software such as antivirus programs are unable to detect new threats, as by the time they are updated to account for a new piece of malware, there are already newer threats available.
AI can combat this ever-evolving threat by using deep learning algorithms in order to cross-check data and apply an ‘if this, then that’ approach to detecting problems. It looks at past occurrences and analyses current and predictive data to form a solid point of reference that detects malware. The more data and malware it goes over, the better it becomes at detecting new malware. This is done at speeds capable of outperforming the competition.
On top of that Ensemble learning is also used. This translates to using a layered approach, where multiple learning models are combined to create one that is more robust. This can boost detection rates and lower errors drastically.
In fact, machine learning has an up to 92% effectiveness rate.
Of course, all of the above is done under human supervision, where the Cyber Security team can focus on the AI and the real attacks, rather than on false positives.
Endpoint security is becoming absolutely necessary.
Cyber-attacks haven’t only increased on corporate networks. Most people have spent a lot of time working from home in the last two years. This has led to the fast development of new malware and ransomware, capable of consistent attacks that businesses have to defend their employees at home from.
Aside from the increasing number of threats, and the ever-adaptiveness of them, business also face an increasing number of endpoint devices – from laptops, to computers, to phones, tablets, and wearable technology. Cyber threats target weaknesses based on user behavior and poor digital hygiene.
This variety of devices and threats can drain a Cyber Security team of their time and resources if they rely on standard practices. Meanwhile legacy software can cause potential disconnects, and zero-day exploits can targeted antivirus programs. As mentioned above, false positives also drain time and resources.
That is why AI and ML have become more and more in demand when it comes to endpoint security. The ability to examine every device, and monitor activity is crucial.
Especially given that 80% of ransomware attacks were caused by users unknowingly infecting their device by clicking on an unauthorized link or file.
The information to be processed is too large to be examined by humans, but AI can do that easily.
In conclusion, just like any tool, AI and ML are best used when backed up by experience and knowledge. While AI technology won’t eliminate the need for a dedicated Cyber Security team, they will make its job much easier.
You can rely on Cosmos Thrace to give you the security that only AI can afford. With our hands on experience, we will support you on every step of the journey to security.