Adaptive Cybersecurity: The Adaptable Retrainable Firewalls.

One remembers the times of cybersecurity when a firewall was simply a gatekeeper, which blocked what was bad and allowed what was good using fixed rules? Ok the digital world has evolved and so do the threats. The modern cyberattacks are shape-shifters and are continuously changing to bypass conventional protection mechanisms. This is where adaptive cybersecurity is involved, and dynamically retrainable firewalls are at the center of this. These are not the firewalls of your grandfather, but rather smart systems that learn, adapt and anticipate threats as they happen. What makes these next-generation defenses so radical and why they are becoming indispensable to the current protection will be explored in this blog post

The History of dynamically retrainable firewalls.

Further than Deterministic Rules: Why Retrainable Firewalls are Necessary.

Conventional firewalls work on a predefined rules list. Provided that the traffic fits a rule that is known to be bad, it is blocked; correspondingly, it is permitted to pass over a rule known to be good. This is good with familiar threats, but it does not do well with unfamiliar, unknown or very dynamic attacks. The nature of modern threats, which are usually driven by the AI itself, can readily change their approach, and thus quite new defenses become outdated almost immediately after they are implemented. The new game with dynamically retrainable firewalls is that it does not rely on these set of rules but, with each arrival of new data, continuously updates its protective policies and responds to them without human intervention.

Machine Learning: Driving the Adaptive Firewall Brains.

So, how do firewalls get "smart"? Machine Learning (ML) is the answer. Rather than human administrators penning out each and every rule, ML-algorithms are informed by incredibly large volumes of network traffic information- both legitimate and malicious. The firewall then applies this information to determine patterns, and detect anomalies and even anticipate threats. Upon the appearance of a new threat or the variation of network conditions, the ML model can automatically retrain itself with the adaptation of its policies and rules on-the-fly. This enables the firewall to automatically make itself as effective as possible, thus a proactive instead of a reactive security device.

On-the-fly Adaption and Policy Optimization using Dynamic Firewalls.

What about a security system that does not simply block a known virus, but actually learns the nature of new and never-before-seen malware and develops a new defense rule dynamically. Dynamic retraining is that powerful. This is not limited to malware but a dynamic firewall can adjust to a changing user behavior, new applications, or change in network topology (adding new cloud services). Its continuous optimization of its policies guarantees that its security measures will be always up to date, and efficient against the most recent threats, which will lower the time interval of vulnerability that most attackers can take advantage of.

The importance of dynamically retrainable firewalls to your organization.

There is a strong benefit of adopting dynamically retrainable firewalls. They drastically decrease the amount of manual labor needed to handle security policy management, and allow IT employees to work on more important projects. More to the point, they offer an enhanced security against advanced attacks, such as zero-day exploits and polymorphic malware that can easily evade the conventional security systems. With the growing sophistication of cyber threat represented by the use of intelligent and automated threat systems, it is not only that having an equally intelligent and adaptive defense system is not only an advantage, but it is rapidly becoming a prerequisite to effective organizational security.

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