The Important Role of Artificial Intelligence in Network Defense

Artificial Intelligence (AI) is rapidly transitioning from a newcomer to a critical component. Just as AI has become integral to self-driving cars and chatbots, its role in InfoSec is no longer a luxury but a necessity.

The imperative for AI in cybersecurity stems from the relentless expansion in the variety and scale of cyberattacks. Traditional security measures struggle to keep pace with the sheer volume and sophistication of threats. AI, with its ability to swiftly analyze vast datasets, detect anomalies, and adapt to evolving attack patterns, fills this crucial gap.

In this dynamic cybersecurity environment, AI is not just an asset; it’s a linchpin that will continue to play an indispensable role in safeguarding digital assets and infrastructure against an ever-growing array of threats.

Cloud Services

AI Can Detect Zero-Day Attacks Better

A zero-day attack is one that hasn’t already been logged by a threat intelligence system that powers a cyber defense tool. For example, if an attacker used ransomware that encrypts a computer’s data at a certain point in time, its threat signature would most likely be shared with dozens of threat mitigation systems. However, a new ransomware could fly under the radar until an attack has been recognized, studied, and reported.

A system powered by AI doesn’t need threat signatures to identify potential attacks. Instead, it can detect a threat based on its behavior or the behavior of the system being attacked. Consider the following simple example: Suppose an AI-powered threat monitoring system regularly logs and studies the amount of traffic heading into and exiting network ports. The system establishes an acceptable baseline, or state, that signifies normal data movement through the network.

But then there’s a sudden spike in data moving out of the network. Because this could signify an attempt at data exfiltration, the AI system could send an alert, shut down certain ports, block the source of the incoming attack, or a combination of all of the above. Essentially, AI and ML can implement what is referred to as a 5D approach—Deter, Detect, Deny, Delay, and Defend. Professionals in the cybersecurity field recognize this as the most effective approach.

AI Enhances Incident Response

AI can respond to threats automatically, saving IT teams many hours every week and focus threat response where it truly matters. For instance, suppose you have a powerful threat detection system that surfaces many threats a day. But because the system is so sensitive, your IT team quickly gets inundated with alerts, resulting in alert fatigue. Conversely, actual threats may be detected too late or even missed. For example, if your system is hit with malware designed to launch an SQL injection, leveraging AI/ML by training the model with historical data, determining which SQL statements are valid and which represent an attack, it can be responded accordingly by distinguishing between the two.

Additionally, AI could be used to filter out the noise, choosing which alerts to send through to the IT team. An AI system can also perform actions to automatically mitigate. In that way, AI can instantly stop a threat that may take a human hours to detect and address.

AI Can Protect Web Apps Far Better Than Humans

A system powered by AI can use machine learning (ML) to detect problematic patterns in how external actors interact with a web application. In this way, it can identify threats and stop them without even having to check in with a human first.
To illustrate, suppose you have a web application that powers an e-commerce solution. If your e-commerce goes down, your online revenue stream stops. Knowing this, hackers try to launch a distributed denial-of-service (DDoS) attack on your web app. This would flood your web server with false requests, making it impossible for the server to respond to authentic customer requests, such as those made during the checkout process.

A Web Application Firewall (WAF) powered by AI can instantly recognize a DDoS attack and determine both how it is being launched and how best to mitigate it. DDoS attacks have become more complex, often managed through a command and control server and launched via numerous edge computing or IoT devices simultaneously. Based on the web application, geo locations of the customers base, AI enabled WAF can rapidly respond to this threat in a comprehensive way by leveraging various techniques such as geo restriction, blocking fake data packets, verifying signatures and by employing different techniques at application layer, it can slow down and eventually stop the attack.

At i-Link Solutions, we understand how to leverage the power of AI to ensure safer, and dependable applications. We also know how to use AI-powered tools to improve your security without hindering your business.

Discover the Power of Artificial Intelligence (AI) with i-Link Solutions today.