The Role of AI in DDoS Detection and Mitigation

A distributed denial-of-service (DDoS) attack causes millions of organizations around the world to contend with low-performance, inoperable, or completely disabled business systems. As the number of DDoS attacks per year continues to skyrocket, companies increasingly search for innovative cybersecurity defenses to rely on.

Artificial intelligence-embedded DDoS protection tools are rapidly becoming the answer to the overwhelming number of DDoS attacks. In this article, we’ll explore how AI is helping prevent DDoS attacks, touching on why this attack vector is so disastrous for businesses and how artificial intelligence is providing a solution.

The Evolving DDoS Threat

Every single year, the DDoS threat becomes more pronounced. According to a recent report, the number of DDoS attacks grew by over 90% in 2023, increasing the total number of attacks dramatically. This yearly trend of a huge increase in the number of attacks follows from 2022’s figure of a nearly 100% increase in DDoS attacks.

Another alarming statistic is that hackers are now targeting a wider spread of businesses. DDoS attacks used to be concentrated on high-risk sectors, like e-Commerce, finance, government, and healthcare. Yet, recent data suggests that attacks now occur in high percentages across almost every industry.

If businesses aren’t prepared for a DDoS attack, they could likely be the next target. One of the reasons that DDoS attacks can be so powerful is that they don’t all look the same. Most commonly, people think of an attack as an overwhelming mass of traffic, which it can be. However, there are actually numerous types of DDoS attacks, each of which poses its unique risks:

• Volumetric Attacks: The classic form of DDoS attacks sends overwhelming amounts of traffic to a system, completely stalling the ability for employees and customers to access the systems.
• Application-Layer Attacks: These DDoS attacks focus on the application layer of systems, causing them to overload and be unable to complete tasks.
• Reflection Attacks: Hackers take control of third-party servers, and then use them to launch mass traffic at sites.
• Protocol Attack: Attacking the network protocol of a system to slow it down to an inoperable rate.

If businesses do not understand how to defend themselves against all of these potential DDoS attacks, then they could be the next company to add to the long list of targeted companies in 2024.

How AI Aids in DDoS Protection

Artificial intelligence is one of the most precise solutions when it comes to fighting back against the rising number of DDoS attacks that a business may face. One of the main reasons that DDoS attacks are able to impact systems is that hackers develop new attack patterns before launching traffic.

Traditional security systems use past attacks as a point of reference. When they identify a pattern in traffic that’s associated with DDoS, they block the attack, using pattern recognition to stall attackers. Yet, when a hacker then changes their attack pattern, many traditional security tools are unable to identify the attack in time, reducing the window of opportunity for security teams to react. In these circumstances, it is typically too late, with a DDoS attack successfully overwhelming defenses and rendering systems inoperable.

Artificial intelligence, on the other hand, provides real-time analysis of traffic, using its ability to learn new attack patterns and identify distinct vectors to more effectively stop DDoS attacks. Artificial intelligence helps in DDoS protection in several ways:

• Precise Traffic Filtering: The core duty of a tool that aims to prevent DDoS attacks is to determine the difference between real and botted traffic. Artificial intelligence tools don’t have to make generalized decisions; rather, they can analyze millions of concurrent connections on a granular level. This level of detection allows them to make more precise traffic filtering decisions, blocking any traffic that AI deems to be botted while still allowing real users to access your applications.
• Adaptive Learning and Threat Expansion: Artificial intelligence and machine learning technology use adaptive learning strategies to continually enhance their own knowledge of security threats, patterns, and potential attacks. By training on thousands of unique cases, AI DDoS detection tools can build up a comprehensive knowledge of not only precious threats but also what future threats may look like. With this approach, businesses can future-proof their security.
• Real-Time Traffic Pattern Analysis: AI tools provide 24/7 security, monitoring access networks and application layers to continuously check for potential suspicious traffic. This significantly decreases the need for real security agents to monitor traffic, freeing up their time for higher-ROI security tasks, like penetration testing.

As artificial intelligence tools continue to develop, they will only become more powerful at analyzing potentially botted traffic and ensuring that it is unable to connect to your servers. This powerful solution will help reduce the number of DDoS attacks that the average business encounters, protecting servers from malicious traffic.

Choosing the Right DDoS Solution

Cybersecurity systems that seamlessly implement AI into their existing security posture are able to better identify, respond to, and mitigate DDoS attacks when they occur. Artificial intelligence offers a powerful solution for DDoS attacks, providing evolving pattern recognition and advanced system monitoring to block traffic in its tracks.

As businesses continue to fortify their security defences, finding a DDoS solution that makes use of AI is the most effective method of keeping your business safe. Where possible, look toward security solutions that integrate new technology to enhance your security posture, expand threat intelligence, and create comprehensive security architecture.