How AI Enhances Cybersecurity by Automating and Augmenting Human Capabilities

Cybersecurity professionals have challenging, demanding jobs that require them to work in fast-paced environments while dealing with an ever-changing internet security landscape. However, artificial intelligence (AI) can help workers in this industry save time and feel less stressed. Here are some of the most compelling AI cybersecurity use cases.

Incident Categorization

Most business owners, marketers and designers occasionally become so busy that they don’t have as much time as they’d like to devote to specific tasks. Sometimes, such circumstances result in them delegating duties to others with more time or skills. Cybersecurity professionals can do the same if they use AI tools to group potential threats, helping them determine which ones to tackle first.

This approach is particularly valuable for small cybersecurity teams or those where members often become overwhelmed by the seemingly continuous alerts received. Although those real-time notifications help prevent emerging situations from getting out of control, some are false alarms or the issues are not serious enough to warrant immediate attention.

Artificial intelligence algorithms can learn what constitutes regular network activity and group all anomalies by severity level. That approach helps cybersecurity specialists understand which incidents to focus on first and gauge how many colleagues they may need to investigate a particular matter.

Many company leaders are dealing with a long-term skills shortage, making open cybersecurity roles harder to fill. Artificial intelligence cannot solve the worker deficit, but it can make the effects less acutely felt within overworked teams.

This AI cybersecurity application is also beneficial for organizations with many IT team members who are new to the workforce or only have a few years of experience compared to others. Managers could look at all potential incidents on a real-time dashboard, assigning people to investigate them based on severity level and the worker’s experience. Alternatively, they may pair lesser-experienced employees with seasoned veterans to maximize the learning opportunities.

Behavioral Analytics

As password breaches become increasingly common, many access control managers look for more reliable ways to secure company assets. Some use biometrics to determine if corporate network users suddenly start displaying unusual behaviors. Such cases could indicate a hacker trying to impersonate an authorized user.

AI models create and analyze databases, using the information to make predictions. Those that work with machine learning can rely on previous data or decisions. So, machine learning models can improve through regular use, not requiring ongoing formal training. This capability is useful when cybersecurity professionals want to verify users’ identities with methods other than passwords.

An AI cybersecurity tool that uses machine learning and biometrics might analyze login attempts in the background, tracking specifics such as mouse movements, clicks and typing speeds. It could then use the associated data to create individual profiles for each authorized corporate network or app user.

Some companies offering such products even have data based on how fast someone typically types based on their age. If an AI detector finds a significant deviation from the norm, an online interface might prevent someone from gaining access. However, some people feel concerned about tools wrongly locking them out, especially since many banks use these tools on their online platforms.

Imagine if a broken arm or wrist fatigue caused a rightful account user to start typing much slower. Artificial intelligence could flag their access attempts as suspicious, causing confusion and concern for the person.

Problems could also result because not all AI tools can reveal how they came to certain conclusions. If a company leader wants to use behavioral analytics as part of a cybersecurity strategy, they must try to balance strong security and convenience.

Automated Prevention

Cybersecurity professionals should ideally stop intrusion attempts before they start. Many AI cybersecurity platforms have such capabilities. They support human expertise by allowing people to set triggers that cause specific automated options. For example, some AI-powered email screeners automatically quarantine messages with unusual attachments or those from a known dangerous source.

Such tools could also prevent ransomware. These attacks can be incredibly damaging because they restrict file and network access until someone from the affected organization pays a ransom. Cybercriminals often demand staggering amounts, too — the average ransom paid was $570,000 in 2021. However, the ransom for another attack that same year was $50 million.

How those requests get handled is often complicated. Some policies forbid providing the ransom or engaging with cybercriminals. In other cases, people at the affected organizations are so desperate that they pay and hope the action will get them the desired results.

A payment doesn’t guarantee restored access. Additionally, even if the files do get unlocked, cybercriminals might target the same business soon after an initial attack, knowing they’ll likely receive payment. Cybersecurity experts can set up interfaces that recognize and automatically block the types of malware often used in ransomware attacks. Some tools can also restrict what an intruder can do after gaining access to a network, limiting the overall ramifications. 

Possible Shortcomings

People must remember these tools are helpful but not foolproof. Your email provider’s spam detector likely works with AI. It learns which messages you deem important and sends suspected junk mail to a separate folder. However, most users have had issues where AI marked genuinely vital emails as spam.

This example reinforces how cybersecurity professionals must treat artificial intelligence as a technology that assists in their work but does not take it over. A good approach is for cybersecurity experts to configure and monitor these tools, intervening when the tech catches unusual activity.

Will You Use AI Cybersecurity Tools?

These are some of the many ways people can rely on AI to make cyberattacks happen less often. Since cybercrime occurs with increasing frequency and the results can be so damaging that they shut down your business, it’s always wise to consider the most appropriate ways to combat it. Even if you don’t start using AI cybersecurity tools immediately, keep an open mind about them and what they can do.