Technology is constantly evolving and changing how industries operate. Zero-trust security is making big waves in the world of cybersecurity. Many businesses quickly adopted this practice to have peace of mind while their employees work safely from anywhere.
Zero-trust security requires robust technology to operate effectively, and with the rise of artificial intelligence (AI) and machine learning (ML), it was the obvious choice. Here’s what to know about zero trust and how AI empowers it.
What Is Zero-Trust Security?
Zero-trust security uses the principle that any user — whether the device is in or outside the network perimeter — must be continuously verified to gain or retain access to a private network, application or data. Traditional security does not follow this practice.
Standard IT network security makes obtaining access outside its perimeter hard, but anyone inside is trusted automatically. While this worked great in the past, it presents businesses with modern-day challenges. Organizations no longer have their data in one place but on the cloud.
People transitioned to remote work during the COVID-19 pandemic. This meant data stored in the cloud was accessed from different locations and the network was only protected with a single security measure. This could open companies up to data breaches, which cost an average of $4.35 million per breach globally and an average per breach of $9.44 million in the United States to rectify in 2022.
Zero trust adds another security layer that provides businesses peace of mind. Zero-trust security trusts no one — it does not matter if they are out or inside the network — and continuously verifies the user trying to access data.
Zero trust follows four security principles:
- Access control for devices: Zero trust continuously monitors how many devices are trying to access the network. It determines if anything poses a risk and verifies it.
- Multifactor authentication: Zero-trust security needs more proof to provide access to users. It still requires a password like traditional security, but it can also ask users to verify themselves in an additional way — for example, a pin sent to a different device.
- Continuous verification: Zero-trust security trusts no device in or outside the network. Every user is continually monitored and verified.
- Microsegmentation: Users are granted access to a specific part of a network, but the rest is restricted. This prevents a cyberattacker from moving through and compromising the system. Hackers can be found and removed, preventing further damage.
3 Ways AI and ML Can Empower Zero Trust
Zero-trust security runs more effectively with AI and ML. This allows IT teams and organizations to protect their networks properly.
1. Provides Users With a Better Experience
Enhanced security comes at a cost that can be a downside to many companies — the user experience. All these added layers of protection provide many benefits to the organization. However, it can force people to jump through many hoops to obtain access.
The user experience is essential. People that don’t follow protocol could damage the organization. This is a major issue that ML and AI address.
AI and ML enhance the entire experience for legitimate users. Previously, they may have waited extended periods for their request to be approved because requests were manual. AI can speed up this process immensely.
2. Creates and Calculates Risk Scores
ML learns from past experiences, which can aid zero-trust security to create real-time risk scores. They are based on the network, device and any other relevant data. Companies can consider these scores when users request access and determine which outcome to assign.
For example, if the risk score is high but not enough to indicate a threat, additional steps can be taken to verify the user. This adds an extra layer of security to the zero-trust framework. These scores can be taken into account to provide access.
Here are four factors these risk scores can take into consideration:
- What location the device is requesting access from and the exact time and date this occurred
- Out-of-the-ordinary requests for access to data or unexpected changes to what someone can request access to
- User details, such as the department worked in
- Information about the device requesting access, including security, browser and operating system
3. Automatically Provides Access to Users
AI can allow requests for access to be granted automatically — taking into account the risk score that has been generated. This saves time for the IT department.
Currently, IT teams must verify and provide access to every request manually. This takes time, and legitimate users must wait before approval if there is a huge influx of requests. Artificial intelligence makes this process much quicker.
AI Making Zero Trust Better
AI and ML are necessary in zero-trust security. They provide many benefits and streamline procedures to provide a great user experience while protecting the organization effectively. Strict security usually has drawbacks, but adding AI and ML provides companies and their clients with many advantages.