4 Ways AI Driven EDR Secures Personal Devices

AI has been making waves in the world of cybersecurity for a long time now. Thanks to the emergence of threats that use AI to learn defense systems and adapt, solutions providers have done the logical thing and begun using AI to adopt a robust posture.

AI has been making waves in the world of cybersecurity for a long time now. Thanks to the emergence of threats that use AI to learn defense systems and adapt, solutions providers have done the logical thing and begun using AI to adopt a robust posture.

Cybersecurity tends to get spoken about in terms of enterprises and their need to secure data. However, individuals need to secure their devices and data as well, thanks to the large amount of personal data that we store. Furthermore, our browsing patterns and app usage reveal a lot of information about us that malicious actors can use.

An AI-driven EDR like RasonLabs’ RAV EDR is one of the best solutions for securing personal data on devices. Here are 4 reasons why this is the case.

Continuous Protection

One of the qualities that makes the RAV EDR solution distinct from others is the former’s continuous protection ability. An AI-driven solution is always on, meaning it constantly scans networks for threats and learns how those threats are evolving. It can also spot patterns in the way a device or network is being threatened and nip issues in the bud.

Typically, these solutions are backed by a cloud-based threat intelligence center that acts as a central database that logs all threat-related data. By remaining connected to this database, the local instance of an EDR is always up to date and can detect threats entering a network.

AI-backing in this context is essential because threats evolve quickly, often according to the unique vulnerabilities a system has. For instance, a malicious actor can deploy AI to learn the vulnerabilities and strengths of a security system by deploying a series of attacks against it.

As the system repels each attack it involuntarily provides intelligence to the attacker, and eventually, the malicious AI has enough data to understand where to attack. If the security system is embedded with AI, it will spot such attacks quickly and subvert them without disclosing any vulnerabilities. This dynamic security posture is the key to robust cybersecurity.

Root Cause Analysis

One of the most important functions a cybersecurity solution can offer is a robust root cause analysis process. Whether a threat was successful or not, a system needs to determine where it originated from and whether any user behavior was the reason for its emergence. For instance, did the user download a corrupted file that ultimately breached cybersecurity?

More importantly, is there a chance of this occurring once again? A robust root cause analysis engine will determine where the error occurred from and can provide recommendations to stop it from happening again. AI engines work their magic by learning patterns.

In this case, RAV EDR will learn user patterns and can pinpoint areas that are hampering cybersecurity. For instance, the user might be visiting a few websites that appear safe but have serious issues. These websites might potentially inject harmful code onto the user’s device.

By learning browsing and usage patterns, the AI can prevent further attacks from happening. This method of learning usage patterns is also useful when monitoring system usage. If the security platform detects unnatural system usage, it can dive deeper and unearth any apps and processes that are running in the background. There’s a high probability these apps might be malicious.

Thus, root cause analysis driven by AI is an important feature in all robust EDR solutions.

Built for Everyone

While companies can hire personnel who are cybersecurity experts, individuals need a system that handles everything automatically. This means the platform’s UI and functionality must be simple to understand and must not overwhelm the user with technical information.

For instance, if a user needs a degree in computer science to understand some of the terms and choices within the security app, the app isn’t of much use. Thankfully, this isn’t the case with the RAV EDR solution. Not only is it built for users who lack deep knowledge, but it can also be used by people who are knowledgeable and wish to dig deeper.

Thanks to this flexibility, users of all levels can rest assured that they’re always protected by top-notch systems.

New Threat Analytics

Cybersecurity is an ever-changing field, and constant threat analysis is the only way to stay a step ahead of malicious actors. AI-driven solutions can draw from a central library of threat data as previously mentioned. However, these solutions are also powerful because they can run analytics on existing data and uncover potential threats.

Analytics-driven protection ensures that individual users can rely on enterprise-grade protection on their devices at all times. When coupled with the other features listed in this article, opting for an AI-driven EDR solution is a no-brainer. Given the threat landscape, it might even be a necessity.

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