How You Can Improve Your Cybersecurity With The Help of AI

For the last few decades, technology has paved the way for numerous political, social, and economic changes. Online shops and smooth banking operations have drastically changed our shopping habits. Healthcare is being reshaped by modern microscopes able to find a new medication for once-incurable ailments. Meanwhile, politicians announce presidential campaigns over Twitter with carefully selected keywords for SEO value.

But one branch of modern technology promises to change the world as we know it – Artificial Intelligence. It’s one of the hottest topics among technology analysts and developers. Can it actually bring more prosperity and make our lives easier? Or do apocalyptic Hollywood-style scenarios of rogue AI actually hold merit?

There are well-informed opinions on both sides. Nevertheless, AI is already successfully utilized for various improvements. If you want to learn what AI is and why it works for creative industries, check out our other blog post. In this piece, we will take a look at AI from a cybersecurity perspective.

How Does AI Relate to Cybersecurity?

Cybersecurity is an extremely complex discipline that deals with a whole range of other branches. From networking to social engineering to ethical hackers, futuristic cyber weapons – there’s just so much going on.

Cybersecurity is becoming something that every Internet user knows of. According to Cybersecurity Ventures 2020 statistics, global cybersecurity costs will reach $10.5 trillion in 2025, growing 15% yearly. Moreover, the FBI reports that in 2020 there were 2000 Internet crime complaints per day.

The last couple of years have been challenging for online safety. Hackers have successfully exploited the Covid-19 crisis, improving their Phishing scams to focus on personal healthcare. Simultaneously, ransomware spreads like wildfire, paralyzing Ireland’s healthcare and US oil industries and causing massive damage. Companies and government institutions have therefore become ever more wary of their cybersecurity policies and have been busy implementing various additional layers of safety such as better password management practices and complex data storage solutions.

However, as cyberattacks mount up, it has become evident that a purely rule-based method of recording and tackling these threats can sometimes no longer hold up. Instead, AI-based Machine Learning algorithms have displayed a far greater complexity and flexibility in helping cybersecurity specialists anticipate and counter such attacks effectively. A key element is how to mitigate third party risk from vendors and other external parties.

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AI-Powered Cybersecurity Solutions

AI excels at analyzing enormous amounts of data. Machine Learning algorithms can learn from Big Data without significant human interference, which is perfect for cybersecurity software. Let’s take a closer look.

According to Verizon’s 2022 Data Breach Investigations Report, human error caused 82% of data breaches. The weakest link in your workplace security system is the employee. But do not rush to conclusions. Even experienced cybersecurity pros fall for the most modern social engineering scams, Phishing being one of them. 

Phishing heavily relies on Big Data. Cybercriminals scrape the web to gather personalized knowledge that fuels their email content. Hackers analyze speech and writing patterns and produce convincing emails that are easy to fall for. However, the same applies to AI-powered cybersecurity solutions. Contemporary AntiVirus software and VPNs implement real-time protection features that use ML algorithms to broaden the defense perimeter. They can recognize fabricated speech patterns that seem perfectly natural to the human-eye. Such software will detect Phishing emails immediately, mark them as dangerous, and send them to be reviewed by cybersecurity personnel.

Another effective practice to avoid email-based threats is having a solid DMARC policy. By enforcing authentication, DMARC helps prevent email spoofing and impersonation, as unauthorized emails are less likely to reach recipients’ inboxes.

It’s nearly impossible to go over thousands of cyber incidents manually. Moreover, some come from automated bot networks, and going over each and every one would be a waste of time. ML-powered cybersecurity software analyzes the whole traffic simultaneously. It immediately separates bot attacks from the rest and can issue alerts for cybersecurity personnel to analyze specific issues. For instance, a tool like Intruder’s website security scanner can easily identify weaknesses in the sites it scans. Moreover, it learns to identify such threats quicker and more efficiently and can automatically apply adequate solutions once verified by a human administrator. When exploring cybersecurity with the assistance of AI, it’s important to understand the role of Privileged Access Management

Social engineering is effective because it exploits human error. For example, domain or name spoofing is relatively simple. Changing the letter “O” to “0” or “w” to “vv” is effective when a person is browsing through a smartphone, and the difference is barely noticeable. AI cybersecurity software quickly recognizes these miniature changes.

Moreover, suppose your employees receive a Phishing email disguised as a letter sent from your device. In that case, AI will analyze the speech pattern, sender’s name, as well as the backlink structure and compare it to its vast database of available Phishing software capabilities. It will achieve within minutes what an experienced cybersecurity professional would in a few hours. 

Last Word

It’s hard to imagine that AI will substitute for a human employee. We are sure, however, that it will be an invaluable tool to minimize the risks of human error. AI-powered cybersecurity software excels at detecting sophisticated threats and navigating effortlessly through Big Data. Using such software might be a game-changer for your business security and prevent unnecessary troubles in the future.

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