The frightening truth about increasingly common cyber-attacks is that most businesses and the cybersecurity industry itself is not prepared.
Beyond the lack of preparedness on the business level, the cybersecurity workforce itself is also having an incredibly hard time keeping up with demand. By 2021, there are estimated to be an astounding 3.5 million unfilled cybersecurity positions worldwide.
That means cybersecurity professionals will have to compensate for those empty slots, either by working harder (though there’s only so much you can reasonably do) or by working longer hours. In fact, a survey by Spiceworks found that knowledge workers like IT professionals worked on average 52 hours a week. An overworked cybersecurity team means it can be tough to respond to threats appropriately and effectively.
What Can AI Do for Cybersecurity?
Given the state of cybersecurity today, the implementation of AI systems into the mix can serve as a real turning point. These systems come with a number of substantial benefits that will help prepare cybersecurity professionals for taking on cyber-attacks and safeguarding the enterprise.
New AI algorithms use Machine Learning (ML) to adapt over time. Simon Crosby Co–founder and CTO at Bromium, writes that ML makes it easier to respond to cybersecurity risks. New generations of malware and cyber-attacks can be difficult to detect with conventional cybersecurity protocols. They evolve over time, so more dynamic approaches are necessary. Cybersecurity solutions that rely on ML use data from prior cyber-attacks to respond to newer but somewhat similar risk.
Another great benefit of AI systems in cybersecurity is that they will free up an enormous amount of time for tech employees. AI is most commonly used to detect simple threats and attacks. Given that the simplest attacks usually have the simplest solutions, the systems are also likely be able to remediate the situation on its own.
How can cybersecurity experts leverage AI? They depend on intelligent automation to trigger risk red flags that humans may not have the time and resources to search for. Steve Grobman, CTO at McAfee states that AI won’t make human cybersecurity experts obsolete, but it is reducing the need to have as many on staff and is increasing their effectiveness.
Another way AI systems can help is by categorizing attacks based on threat level. While there’s still a fair amount of work to be done here (52% of cyber professionals say systems aren’t accurate enough), when deep machine learning principles are incorporated into your systems, they can actually adapt over time, giving you a dynamic edge over cyber terrorists.
AI systems that directly handle threats on their own do so according to a standardized procedure or playbook. Rather than the variability (and ultimately inaccuracy) that comes with a human touch, AI systems don’t make mistakes in performing their function. As such, each threat is responded to in the most effective and proper way.
Unfortunately, there will always be limits of AI, which is why Grobman states that human-machine teams will be key to solving increasingly complex cybersecurity challenges:
“If you think about other areas that are taking advantage of machine learning or AI, very often they just improve over time. A great example is weather forecasting. As we build better predictive models for hurricane forecasting, they’re going to continue to get better over time.
“With cybersecurity, as our models become effective at detecting threats, bad actors will look for ways to confuse the models. It’s a field we call adversarial machine learning, or adversarial AI. Bad actors will study how the underlying models work and work to either confuse the models — what we call poisoning the models, or machine learning poisoning – or focus on a wide range of evasion techniques, essentially looking for ways they can circumvent the models.”
According to a Workfront report, more employers are depending on automation to solve their most pressing challenges. Cybersecurity professionals are among the employees using automation to utilize their time more effectively and bolster job performance.
AI: The Future of Cybersecurity
We’ve never faced more varied or far-reaching cyber threats than we have today. What’s worse is that these attacks are becoming more common, more sophisticated, and more impactful. When you add a dwindling cybersecurity workforce into the mix, the outlook isn’t great.
However, AI systems can help address some of those problems and ultimately give your business an advantage when facing a cyber-attack.
Cybersecurity solutions that rely on AI can use existing data to handle new generations of malware and cybersecurity attacks.
Ryan Kh is an entrepreneur & startup investor. Founder of Catalyst For Business and managing editor for SmartDataCollective.com. He is passionate on covering topics like big data, data security, business intelligence & entrepreneurship.