How AI Will Help Empower SMB Cybersecurity

Since large language models like ChatGPT have become mainstream, Artificial Intelligence (AI) and its role in our day-to-day are on everyone’s mind. Much of the attention around AI has been about its potential negative impacts on security. However, AI has already demonstrated that it has the potential to do a lot of good in protecting customer data, and its relative affordability makes it ideal for the needs of SMBs. AI can pick up on patterns and recognize inconsistencies far faster than humans can. With that said, we’ve compiled a list of ways that AI is already improving cybersecurity and how it will continue to do so in the future.

Pinpoint Vulnerabilities

SMBs are targeted nearly as much as larger enterprises — to the tune of 43% of all cyberattacks. One of the reasons smaller businesses are often targeted is because hackers know they might not have the resources to properly secure their networks. On-site IT teams can be expensive and monitoring your security takes a lot of time and effort. However, AI has the potential to stay up to date on the latest threats and identify potential vulnerabilities.

AI machine learning opens the door to address vulnerabilities before a system is exploited. In the coming years, AI may be able to scan code and applications to identify weak points and make corrections quickly. Through User and Event Behavioral Analytics (UEBA), we may also see AI machine learning pick up on out-of-place user behavior that can signal an attack.

Predict Attacks Before They Happen

The most common way that hackers gain access to company systems is by logging in with stolen credentials. It’s an incredibly effective way to access your network because they log in like everyone else and rummage around without anyone knowing. This is particularly worrisome for SMBs that have switched to a hybrid or remote work model in the last few years. With so many devices out of the office, it just takes one lost or unattended phone or laptop for hackers to sneak in and get what they need.

However, through UEBA, AI machine learning may be able to pick up on out-of-place user behavior before any real damage is done. For example, say an employee clicks an email link that kicks off a phishing scam. AI will be able to pick up on the change in user behavior and alert IT to the issue before any damage is done. Overall, AI-assisted cybersecurity has the potential to go through huge amounts of data in a fraction of the time, allowing us to identify patterns that will likely lead to a cybersecurity attack.

In traditional cybersecurity, an attack will happen, and companies or IT security teams will make note of the signatures and indicators that led to the attack. From there, they can create a viable countermeasure. This is great for addressing future attacks, but only after they occur. What about those signatures that haven’t been discovered yet?

According to the Institute of Electrical and Electronics Engineers (IEEE), modern signature-based techniques can detect about 90% of threats. Not bad! But by combining current signature-based techniques with AI, we may see up to a 100% detection rate, with AI quickly identifying potential indicators and traditional methods ruling out false positives.

Respond to Incidences Faster Than Ever

Until now, we’ve talked about how AI can prevent attacks, but what about when an incident does happen?

Since AI has already demonstrated that it’s good at picking up on patterns, it would be just as easy for it to run incident response processes quickly to neutralize threats before they do too much damage.

By handing over cyber incident planning to AI, these processes will become far more automated than ever. AI algorithms will be able to analyze potential threats, look into breaches, and make recommendations to security teams to keep business data safe.

Improved Authentication

Currently, multifactor authentication is one of the best ways for SMBs to protect themselves from unapproved sign-in attempts. However, hackers are tricky and are always looking for ways to bypass these systems and present themselves as trusted entities. AI machine learning may provide a way to detect when an unauthorized individual attempts to bypass authentication systems through user behavior patterns and biometric data.

Combined with some of the previous cybersecurity measures we’ve listed above, this can provide a more holistic security environment that neutralizes threats before and as they are happening.

Identify Malware

Since the days of dial-up, malware has plagued internet users. In today’s environment, SMBs still have to be aware of malicious spam containing malware to steal credentials of infected computers with nasty viruses.

Training your employees to identify these types of emails is paramount, but AI-assisted advanced malware detection may be able to add an extra level of protection, identifying malicious programs based on several criteria. The potential in this area is massive, as AI can process huge amounts of data and pick up on patterns that are nearly impossible for humans to recognize. For example, AI machine learning can learn to identify malware through certain file characteristics, behavioral analysis, and network traffic.

AI’s potential to do good will certainly be very attractive to businesses looking to protect their data and their customers’ data. Cisco is already using AI to help SMBs enhance their cybersecurity and help teams automate complex workflows. Until AI becomes more widely used, Cisco will track its progress and continue to integrate the best solutions into our range of security products. If you have any questions about how to better protect your company from threats, contact a Cisco expert today, and we’ll be happy to find the right fit for your SMB.

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