How AI Can Help Stop Cyber Attacks: Our Guide

As companies are pulled deeper into the digital age, the need for protection against cyber threats is imperative. In fact, a recent study shows that one cyber attack happens every 39 seconds.[i] Artificial intelligence (AI) is an effective strategy for thwarting the growing number of attacks levied at organizations today—like fighting fire with fire. Not only is AI increasing the speed and accuracy of your defense, but it also saves you time and resources. This guide will lay out how it works.

How does AI fit in the world of cyber attacks?

In the past, monitoring cyber security threats was a painfully manual task. The time spent monitoring and acting on these attacks was labor-intensive, and the results were less effective. The introduction of AI into this space has transformed the entire process, optimizing our ability to detect and fight off threats. By automating the defense, companies can lay a foundation of protection, and trust the technology to identify these threats before they become attacks.

For context into its growing popularity, investment in cybersecurity has increased more than ninefold since 2011.[ii] By 2020, two out of three organizations planned to employ AI.[iii] AI’s compounding protection is possible because of its ability to process massive sets of data to detect trends, calculate risks, and take instantaneous action.

How is AI used to make cyber attacks?

As we mentioned earlier, fighting fire with fire is the best way for your company to defend itself against cyber threats. And in this case, it’s because AI is being leveraged by criminals to deploy complex hacking strategies. In the same way AI uses data to recognize threats, it can also be used to identify weaknesses or vulnerabilities. Some criminals can reverse engineer AI models to breach sensitive data and essentially control a company’s cybersecurity. Other times, AI is used to scale a larger operation that scrapes applications, devices, and networks for vulnerabilities. Virtually every tactic a cybercriminal uses can be enhanced with AI.

Real examples of AI thwarting cyber attacks.

While it’s simpler to discuss AI and cybersecurity at a high level, real world applications help contextualize their impact. Leveraging capabilities like machine learning and computer vision, here’s what AI-powered cybersecurity looks like in action:

Fighting spam and phishing

AI allows you to leverage deep learning to detect unsafe correspondence—like emails with hidden content or messages with freshly created domains. Its dynamic analyzation model is more thorough than a manual process and identifies elements that would normally slip through the cracks.

Surfacing anomalies.

Since deep learning doesn't experience the fatigue of a manual process, it can diligently track patterns in data and detect anomalies. The deep learning model tracks suspicious patterns like email send frequency or insider threats. Most importantly, the technology evolves with each new set of data ingested.

Protecting DNS data.

When it comes to cyber defenses like firewalls, criminals have become accustomed to using the domain name system (DNS) to access valuable customer or business information. Since DNS data plays by slightly different rules, it’s often allowed to pass through firewalls—making it vulnerable to attackers. Machine learning AI protects companies from these attacks by analyzing trillions of DNS queries to better understand where the bad actors hide.

Identifying advanced malware.

Deep learning AI has enabled companies to optimize their malware protection strategies by increasing the quantity and accuracy of the data it analyzes. Malware is an actively growing threat to cybersecurity, but AI empowers company defense strategies to grow with it. As each sample of malware passes through the model, the AI becomes stronger.

Authenticity protection.

You’ve visited a website that asks you to create an account to gain access. As a quick data grab, companies use this feature to collect user information with greater regularity. Deploying AI as an extra layer of protection allows users to feel safe authenticating their accounts. Features like facial or fingerprint recognition are popular in this subfield of AI, and quickly support safe access through the additional layer.

Advantages of AI within cybersecurity.

Now that you understand how AI has impacted both cybersecurity and cyber threats, let’s look at some of the advantages of implementing the technology within your organization.

Eliminate process fatigue.

Cybercriminals can be relentless, making slight modifications to their methods with great frequency. As we mentioned earlier, hiring someone to take on this defense can become monotonous—thus leading to fatigue and an increase in human error. AI takes the redundancy out of the equation, deploying a system that doesn't understand the concept of burnout. It also goes above and beyond, handling repetitive tasks while also learning from every piece of data that enters the system.

Process larger amounts of data.

As more organizations move their infrastructures to the cloud, the more important it has become to protect the innumerable swaths of data being exchanged and housed. We’ve reached an inflection point in how we can safely process it all, and the best solution is AI. Automation allows companies to comfortably transfer large sets of data without the concern of a malicious actor hiding in the mass of it all.

Automatic alerts to new threats.

Another aspect of AI that improves the cybersecurity process is the instantaneous nature of finding and reporting a threat. Simply put, AI technology does not need to go through the great level of discernment a person would when deciding whether a piece of data is trustworthy or not. The beauty of automation is its objectivity, and an AI model simply triggers a real-time alert when it finds suspicious behavior. Additionally, AI predictive model finds threats before they even occur.

Disadvantages of using artificial intelligence in cybersecurity.

While AI has shifted the paradigm for cybersecurity, there are a few drawbacks to implementing your own model. For one, there is a financial commitment that comes with launching and operating an AI system. You’ll save money and resources on headcount, but that doesn’t mean the technology is free. Next, it takes a lot of time to gather the variety of malware and anomaly sets to give your model a starting point. To that point, an AI system can surface incorrect findings if it’s not provided with enough data to measure against.

In conclusion: Fight technology with technology.

When it comes to implementing a cybersecurity strategy, AI is a powerful technology that can help organizations stay on top of the growing number of threats. Between identifying attacks before they happen, receiving real-time alerts, and increasing accuracy by eliminating human error—an improved security posture is possible. The results are lower costs, improved efficiencies across your business, and the comfort of knowing your data is protected.

How SailPoint can help you incorporate AI into your cybersecurity deployment.

As your organization considers its own cybersecurity model, SailPoint can help you leverage the power of AI. Learn more about how SailPoint’s identity platform keeps you ahead of security threats with rich machine learning and risk detection while dynamically protecting your company’s data.

[i] https://techjury.net/blog/ai-cybersecurity/#gref

[ii] https://about.crunchbase.com/cybersecurity-research-report-2021/

[iii] https://www.capgemini.com/wp-content/uploads/2019/07/AI-in-Cybersecurity_Report_20190711_V06.pdf

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