It's time to take the first step toward autonomous endpoint security.
an 8 billion dollar market – is the best approach to the onslaught of breaches facing companies of all sizes today. And a sizable portion of that market is now shifting its focus to endpoint security and autonomous response. Why? To understand this, you need to know what we're talking about when we discuss autonomous endpoints.
As the name implies, autonomous endpoints are devices that can self-heal and regenerate their operating systems and configurations through machine learning and automation. This means that autonomous endpoints have AI built in, allowing them to detect, prevent, and respond to a multitude of situations in real time. The best thing about them is that they don't just react after the fact, but at the exact moment an attack is happening or suspicious activity is detected.
This is not everything. Most standalone endpoint solutions provide a central dashboard that provides a comprehensive overview of your entire network and the details and health of each of your endpoints. This way, you not only enjoy the support of a sophisticated automated system to protect your digital infrastructure, but you also have deep insights to better inform your security strategy.
Standalone endpoint security works better than traditional security tools because it offers a different way of working. The underlying algorithm monitors the entire network for suspicious activity to prevent its propagation upon detection and/or execution. All of this is powered by machine learning, a key component of these autonomous solutions, as it is responsible for monitoring, but also because machine learning allows the security solution to learn from your experience.
If you've ever worked with automation-based security software, you may be concerned about the problem that has plagued these applications for years – false positives. For some time, software solutions that used automation to detect unusual behavior often ended up flagging actions that were not malicious. This can quickly become tedious and time-consuming, so applying machine learning to these solutions is the right way to go.
While standalone endpoint solutions cannot eliminate 100% of false positives (an inherent byproduct of the heuristic security model), the presence of machine learning ensures greater accuracy over time. This is why the software development companies behind these solutions recommend a pilot period before full deployment – this allows the system to improve before a full rollout.
All of this means that while standalone endpoint security solutions have not yet reached maturity, it is essential that you consider implementing them now. The reasons for this are twofold. First, you would be facing one of the biggest security challenges in today's networks. And second, you would be planting the seeds of more robust security for the future.
Autonomous endpoint security still has a long way to go to become the more reliable method that is implied by its theory. Mainly, you still have to work on continuous patches that automatically resolve gaps in the digital infrastructure. Assessing the health of all endpoints and blocking potentially harmful behavior is a fantastic start, but combining this with the ability to track applications and automatically patch outdated ones would undoubtedly take this approach to the next level.
Taking the first step
Now that you know a little more about autonomous endpoint security, it would be great to take the first step towards adoption. This means you should look for a standalone endpoint solution that meets your needs, whether you subscribe to an off-the-shelf solution or work with a custom software development company. To determine the best path forward, you must ask yourself the following fundamental questions:
- How is the solution deployed, managed and operated? Is there a centralized management console to monitor all your assets?
- Does the solution cover on-premises and cloud-based endpoints?
- How does software detect and prevent attacks?
- What is your update frequency? Are they applied directly?
- Does it offer offline protection?
- How scalable is the product?
There are more questions you could ask (like the false positive rate of a canned solution or the presence of QA and testing services in development to ensure final quality). The answers to these questions will give you a good starting point for evaluating the offerings before you and whether you should use an out-of-the-box solution or opt for a custom alternative.
In short, the important thing is to take the first step. Closing any existing gaps in your asset management strategy is more critical than ever, as related incidents are growing by the minute. Naturally, you can't just believe that implementing standalone endpoint security solutions will automatically let you off the hook. You will also need to complement these efforts with training for your team, as, unfortunately, the human factor remains the weakest link in any security chain.
