6 Ways AI Is Improving Cybersecurity

By now, we’re all aware that the development of artificial intelligence (AI) and machine learning will shape our future in several ways. But many of us do not know how these technologies will impact cybersecurity.

We find ourselves at a pivotal moment in this digital era — one in which our personal information is at unprecedented risk. The last decade alone was riddled with hundreds of massive data breaches and identity fraud incidents. Today, cyber criminals can achieve their objectives from anywhere in the world, at any time.

Our need for more progressive cybersecurity measures has never been more imperative than now. Fortunately, cybersecurity applications have received numerous technological advancements over the last few years. Chief among these game-changing developments is the introduction of AI and machine learning to the field. Let’s examine how these technologies are augmenting current cybersecurity endeavors.

1. Improving Cyber Threat Detection With Machine Learning

In cybersecurity, foresight is priceless. Detecting cyber attacks in advance can give organizations the time they need to successfully neutralize these incoming threats. And it turns out that the application of machine learning to data analysis can help immensely in identifying them.

Machine learning helps computers learn from and understand obtained data. In turn, systems can adjust and refine algorithms to reach optimal performance. In terms of cybersecurity, this means that machine learning can enable computers to detect threats and anomalies more accurately than any human is capable of doing.

Traditional technology relies too much upon previous results. Often, this leaves it unable to adapt fast enough to hackers’ latest techniques and strategies. And the sheer volume of cyber threats that people face every day is too immense for human-directed systems. On the other hand, AI allows computers to excel at improvisation by adapting faster than ever before.

2. AI-Fueled Phishing Detection and Prevention

Phishing is the fraudulent practice of sending fake messages. Hackers use this all the time; they pretend to be from reputable organizations or groups so that victims either reveal personal information like passwords or install malware. Phishing emails are so common that one in every 99 email messages is believed to be an attempted attack.

Luckily, AI and machine learning play an integral role in mitigating phishing attacks. Besides being able to respond much faster than a human can, these technologies can identify and track over 10,000 active phishing sources. They also allow for swift distinction between fake and valid websites. Because these technologies are now being employed around the world, AI’s knowledge of phishing campaigns isn’t relegated to only one geographic location.

3. Making Vulnerability Management Easier

Every modern business relies on information technology (IT). But keeping your IT safe can be difficult. Just this year, over 2,000 unique cybersecurity vulnerabilities have been recorded. Managing these with only humans would be practically impossible. Thankfully, AI opens up an easier approach.

AI- and machine learning-based systems can efficiently scan for potential flaws in corporate IT systems. And, by incorporating recent relevant information such as dark web forums, hacking trends, and more, these technologies make it simple to stay on top of the latest developments in this field. With all of these insights, you’ll not only know how your vulnerable targets may be attacked, but also when.

4. More Powerful Password Protection and Authentication

Passwords have always been one of the weakest components of security control. In fact, they’re often the only link between cyber criminal activity and our identities. Biometric authentication is seen as a potential alternative for the future, but it’s currently not the most convenient paradigm to employ. AI could change this.

Developers are leveraging AI to improve biometric authentication and eliminate any weaknesses so that it’s more robust. Apple’s facial recognition technology is a prime example of this. Known as Face ID, this system detects a user’s facial features via infrared sensors. Apple’s AI software then produces a sophisticated representation of the user’s face that allows it to recognize key similarities.

Apple is so confident in this technology that it believes hackers have a one-in-a-million probability of bypassing it. This system also works under different lighting conditions and can compensate for changes such as a new hairstyle or more facial hair.

5. Automated Network Security

Security policy development and organization network topography are two essential components of network security. Unfortunately, both take up a monumental amount of time and human effort to fulfill and manage.

Fortunately, AI can automate both of these processes to some degree. By analyzing network traffic dynamics, AI can generate and recommend policies and procedures to fit your unique situation. The amount of time, energy, and money this could save organizations can’t be overstated.

6. More Robust Behavioral Analytics

Similar to our other examples, AI and machine learning can also be employed to improve behavioral analytics by studying your patterns. This allows them to understand how you use your computer and other smart devices. Details can include but are not limited to your favorite online platforms, usual login times, as well as your texting and browsing patterns.

If an algorithm detects unusual actions that are outside your normal patterns, it can lock the culprit of this questionable activity out of your system. Massive shopping sprees, shipping products to addresses other than your own (e.g., why’d you ship that new game console to Beijing if you live in Los Angeles?), a sharp spike in uploads or downloads of files, and even a change in your typing pace can all alert AI to nefarious behavior.

AI and ML Make Smarter Cybersecurity Possible

We hope you’ve enjoyed this list of amazing ways that AI and machine learning are improving cybersecurity. As far as security goes, these emerging technologies have vast potential for sectors such as finance, retail, and healthcare.

Speaking of different industries, stay tuned for our follow-up post to this article! We’ll delve into how AI is preventing data breaches in three large sectors.

In the meantime, what do you think of AI and cybersecurity together? And what cybersecurity measures do you employ to protect your information? As always, let us know your thoughts in the comments below!