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September 26, 2018 - by Synoptek
We’re entering an era of cybersecurity when we need to rely more heavily on machine learning algorithms as our first line of defense against hackers. With the prevalence of AI-powered attacks, a shortage of IT security talent, and an explosion of Internet-connected devices, it’s going to take the speed of machines to counteract this perfect storm increased cybersecurity threats. Yet there’s a darker side to the promise of AI (artificial intelligence). Let’s look at the pros — and cons — of using AI in cybersecurity.
The average mid-sized company experiences roughly. To truly keep your organization safe, someone should check every event, but there’s no way a human could even begin to prioritize and review such a high daily volume of potential threats. That’s where a something — artificial intelligence — comes in.
AIs use computer algorithms to engage in machine learning to safeguard systems against cybersecurity threats. These programs recognize patterns in your system event logs and flag particularly troubling incidents for human review. Computer security algorithms can be broken down into:
For example, Microsoft’s Windows Defender boasts it can stop malware attacks before they happen by using predictive analytics. All this happens in milliseconds-long ping-pong matches of machine against machine. New companies like Chronicle are using AI to scan your entire IT infrastructure and flag unauthorized activities at incredible speeds — and then use machine learning to improve its approach.
Machine learning has been, is, and will continue to be a crucial tool in the fight against spam and phishing emails. Gmail has been using machine learning techniques for nearly two decades. That’s because this massive email service needed to constantly readjust to new hacking and phishing techniques.
But it’s not just the big companies benefiting from machine learning in cybersecurity. AI makes cybersecurity more assessable to a wider range of businesses, which means your business has less expensive and more comprehensive security options in the face of today’s threats.
Now for the bad news: AI is not infallible. In the rush to capitalize on the AI hype, programmers and product developers may overlook some of the threat vectors that could do the most damage. In the got-to-get-it-to-market rush, the likelihood of making unintentional errors is high, so rushed AI might not be as successful as promised.
Plus, the good guys aren’t the only ones with AI capabilities. Hackers who gain access to internal systems can corrupt data so infected code is tagged as clean by AI systems. To protect yourself against these vulnerabilities, you may want to supplement internal teams by working with security experts or provide training on how to spot AI-generated security reports. Whatever you do to address weaknesses in AI, just make sure you’re always keeping abreast of the latest trends in the industry.
It’s not clear if AI is the end all be all answer to help us mitigate future cybersecurity threats. But one thing is certain: we need all the help we can get. Projections suggest cybercrime damages will hit $6 trillion annually by 2021. Having trouble putting that number into perspective?
With this massive threat looming, it’s hard to not turn to AI to act as a sentry for security protocols. While it’s doubtful AI and its machine learning underpinnings are the cure-all for corporate cybersecurity, it can play a crucial role in a well-rounded security system.
Interested in leveraging the power of AI and cybersecurity? Contact an expert at Synoptek today.
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