Page 131 - Cyber Defense eMagazine Annual RSA Edition for 2024

All of this speaks volumes to how well-organized DDoS attacks have become. From financial services to
professional gaming, attackers are not only exploiting new ways to devise attacks, but they now
orchestrate attacks as part of larger campaigns involving reconnaissance, the attack itself, and then the
real-time monitoring on how the attack has performed. The onus is now on organizations to adapt or
continue facing new attacks on critical applications.

Dismantle Attacker Reconnaissance With Adaptive DDoS Strategies

When defending against DDoS attacks, rapid detection is king. That is because in the face of attackers’
reconnaissance strategies, IT organizations need tools to mitigate attacks before they can impact
services. Thankfully, threat intelligence solutions exist that enable enterprises to use machine learning
(ML) from data lakes of known DDoS attack vectors, methods, sources, and behavioral patterns.

Furthermore, data is able to be continuously fed to detection platforms through an intelligence feed in
real-time to aid in detecting most DDoS attacks. When IT organizations 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, since threat actors tend to reuse the same infrastructure again and again. Solutions that
incorporate real-time threat intelligence can also detect zero-minute attacks and changes to attack
vectors based on both software and security team expertise, which is especially important as attackers
probe and exploit network weaknesses. Once an attack is detected and classified, defenders can deploy
an optimal mitigation measure to selectively block the attack with minimal impact to other systems or
operations. The best forms of threat intelligence regularly reference comprehensive lists, such as:

• Active botnets,
• Bad actors,
• Attack behaviors,
• Attack patterns to compare with current traffic traversing networks, and
• Enable automated countermeasures to knock the attacks down.

With DDoS attacks, it is never a matter of if the next one will happen, but rather when it will happen. That
is because bad actors will continue to conduct meticulous reconnaissance missions to try and outsmart
even the most astute security teams. Despite this unfortunate truth, enterprises can stay one step ahead
by relying on decades of attack mitigation counsel from IT organizations that combine that knowledge
with ML algorithms to ensure that business-critical services don’t fall prey to a new DDoS attack. Now is
the time to adapt and remediate evolving threats before attackers can beat enterprises to the punch.
Taking an adaptive approach to DDoS protection will ensure that the reconnaissance efforts of bad actors
are no match for adaptive DDoS defenses.

131