Why Threat Intelligence is Your Best Defense Against DDoS Attacks

Solutions Review’s Contributed Content Series is a collection of contributed articles written by thought leaders in enterprise software categories. Gary Sockrider of NETSCOUT makes a case for why threat intelligence is your best bet against DDoS Attacks.

The rising tide of distributed denial-of-service (DDoS) attacks threatens organizations worldwide that deliver critical access and services. And increasingly, what may seem mundane is indeed incredibly complex. DDoS attacks span countries, networks, and techniques like water finding a path through any available means. A single attack can span dozens of countries and networks. Modern DDoS attacks include reconnaissance, advanced multi-vector attacks, and real-time monitoring for efficacy, leading to adaptations throughout the campaign.

The bottom line is that bad actors continue to find new ways to pull off attacks through evolving vectors. As such, organizations must adopt new strategies, such as advanced DDoS defense and suppression, to combat the growing complexity. That is what we will explore in this article, specifically regarding threat intelligence with real-time visibility capabilities as an IT organization’s best defense against the rapid proliferation of evolving DDoS attacks.

Why Threat Intelligence is Your Best Defense Against DDoS Attacks

The Evolving DDoS Landscape Reinforces Market Need for Threat Intelligence

To provide a snapshot of where we are within the threat landscape, the first half of 2023 saw continued increases in DDoS attacks, with cyber-criminals launching approximately 7.9 million attacks in the first half of the year. That is a 31 percent year-over-year increase with a staggering 44,000 daily incidents driven by ongoing global instability like the Russia-Ukraine war, the Israel-Hamas war, and NATO bids such as Finland being targeted by pro-Russian hacktivists during its bid. Ideologically motivated DDoS attacks have targeted the United States, Ukraine, Finland, Sweden, Russia, and multiple other countries.

The point is that attackers know no geographic boundaries, and their exploits are becoming increasingly common and sophisticated, targeting businesses, organizations, and individuals worldwide. An abundance of targets are ripe for exploitation by threat actors, and the motivations for these attacks can vary widely. From cyberwarfare (Nation-states using DDoS attacks to deny access to critical infrastructure) to hacktivism (attacks to protest or draw attention to their social or political causes), the rationales are virtually endless, as are the attack vectors that bad actors use in their malicious exploits.

What’s more is that threat actors are now also relying more on DDoS-capable botnets, Tor nodes, and open proxy servers to generate and obfuscate the actual sources of direct-path DDoS attacks. There is a renewed emphasis on direct-path attacks and a transition from a nearly decade-long stint of reflection/amplification preeminence. In addition, bulletproof hosting (BPH) providers pose a unique and challenging threat. Their activity is often disguised under a veil of legitimacy; however, due to their willful neglect of community norms, their illicit activities often evade normal responses such as takedown requests. All of this said, the evolution of attack methods only continues to grow month after month, and with these rapidly evolving threats comes the vital need for threat intelligence as an essential part of a DDoS defense strategy to safeguard critical business operations.

The Importance of Threat Intelligence to Mitigate Evolving Attacks

When defending against DDoS attacks and the methods of attack cited above, rapid detection is key to mitigation before it can impact services. What is often misunderstood, however, is the role that real-time threat intelligence plays in an actual DDoS defense strategy. Today, threat intelligence solutions exist that enable enterprises to use machine learning (ML) from rich data lakes of known DDoS attack vectors, methods, sources, and behavioral patterns.

To bring this to life, data is able to be continuously fed to detection platforms through an intelligence feed to aid in detecting most DDoS attacks. When enterprises consider taking this approach to threat intelligence as part of their DDoS defense strategy, it can block as much as 80-90 percent of attack traffic. Solutions of this nature can also detect zero-minute attacks and changes to attack vectors. Once an attack is detected and classified, the solution understands the optimal mitigation method that can be used to selectively block the specific attack.

In addition, an adaptive DDoS protection approach combines intelligent ML algorithms with dynamically updated actionable DDoS threat intelligence. Adaptive DDoS defenses can identify changing attack vectors in real-time based on both software and human security expertise. For example, when an attack is detected, the traffic is further analyzed with real-time visibility to provide additional automated countermeasures. This analysis is continuously updated as characteristics of the attack traffic change.

It is clear that DDoS attacks will continue evolving in both frequency and complexity. By leveraging decades of attack mitigation experience, combined with unparalleled visibility and ML algorithms, organizations can ensure that there is an unimpeded continuity of business-critical services now and in the future. That is why it is critical for organizations to invest in advanced DDoS detection solutions that use actionable threat intelligence and ML to automate the mitigation of changing attack vectors.