Our world is going digital faster than we can ever imagine. Small- to medium-sized businesses (SMBs) are embracing digitalization because of the conveniences and benefits it offers. One area of technology that's making waves among SMB owners is artificial intelligence (AI) and its potential use for cybersecurity. Below are some ways AI can be used to boost your network defenses.
Cyberthreat detection and prevention
With new tricks and mechanisms at their disposal, hackers can perform complex cyberattacks daily that conventional technology can't keep up with. To address this growing issue, cybersecurity companies are looking into AI technology to detect and hopefully thwart potential cyberthreats.
Using complex algorithms, AI can run pattern recognition in software to identify and isolate potential malware before it can enter your system. AI can also use predictive functions designed to identify threats faster than traditional approaches. With the help of machine learning (ML), AI can actively track and identify over 10,000 phishing sources and react to phishing attacks faster than humans can. Using ML can also help in monitoring phishing threats around the globe. Current advancements have enabled AI to differentiate between a phishing website and a legitimate one, reducing your company's risk of a data breach.
Enhancing login authentication
Passwords are security protocols given to your employees to grant them access to your network system. Unfortunately, passwords are very fragile and are easily exploited by cybercriminals looking to steal your company's valuable information. To make matters worse, there are users who are quite lazy when it comes to creating strong passwords, often using the same passwords to access multiple accounts.
That’s why some SMBs are turning to biometrics as an alternative to passwords. Unfortunately, biometrics come with its own set of issues. One example is facial recognition. However, facial recognition can be inconvenient because it can run into issues such as the user having a new haircut or wearing some headgear that prevents the facial recognition software from identifying the user properly. Hackers can even use pictures stolen from Facebook or Instagram to circumvent facial recognition authentication.
The good news is developers are looking into AI to improve the way biometrics is being used for authentication. A good example is Apple's face recognition app called Face ID. Available on iPhone X devices, Face ID uses built-in infrared sensors and neural engines to process the unique facial features of a user. Face ID then creates a model of the user's face using key correlations and patterns.
Apple developers are confident that with this new technology, the chances of fooling the AI using a stolen picture is less likely to happen. Apple also claims that Face ID can successfully map a user's face even under various lighting conditions. Face ID can even adjust to changes such as the user getting a new haircut, wearing headgear, or having thick facial hair.
Drawbacks of AI in cybersecurity
Although AI can offer a lot of potential benefit in the area of cybersecurity, it also has certain limitations. To successfully implement and maintain an AI cybersecurity system, you're going to need a huge amount of data, memory, and computing power, all of which costs money.
Another drawback of AI technology is that hackers can also use it to test and streamline any new malware they're developing. Cybercriminals can take advantage of existing AI technology to create AI-proof malware capable of slipping through the tightest security protocols.
AI still has a long way to go in terms of being an all-around cyberthreat solution, which is why you should look to an established managed IT services provider (MSP) like Refresh Technologies to take care of your network security. Our advanced cybersecurity solutions will effectively fend off both external and internal threats to keep your data safe. If you want to know more about how you can boost your company's network security, give us a call today.
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