Today, there many discussions within the security community about how IT professionals leverage artificial intelligence (AI) to make products smarter and faster. Companies now use AI to address security challenges at a rapid pace, with a 36% increase in spend on generative AI alone by 2030, according to a recent Forrester study.
While it’s encouraging that companies have harnessed the power of AI and machine learning for better automation within security products, make no mistake: malicious actors are doing the same, and organizations need better tools to keep up with attacker sophistication.
Just look at what occurred with generative AI in 2023. While the majority of people using generative AI have no malicious intent, bad actors are using it to create malicious code, DDoS attacks, phishing schemes, and ransomware. As generative AI tools continue to grow in popularity, IT decision-makers must also consider how to harness its powers for good to improve efficiency in security throughout an organization. Most important, they must also uplevel the tools they offer businesses to better automate threat detection and response.
Ultimately, IT organizations need to automate elements of their jobs into their threat mitigation tools so they can more quickly conduct threat analysis – ideally, in real-time. All that said, now’s the time for IT organizations to think about investing in new tools to automate threat analysis to stay one click ahead of bad actors, who only continue to get more sophisticated with each passing month.
Intelligent DDoS mitigation for optimal defense
The old days of simply blocking malicious traffic floods with access control lists or blackholing traffic are no longer the sole means of thwarting bad actors. An intelligent DDoS mitigation system that can stop numerous types of DDoS attacks (direct-path volumetric, carpet-bombing, state exhaustion) has become the new standard for managing a more effective DDoS defense strategy.
Because of the variety of attacks and the evolving vectors that bad actors use to execute and automate their attacks, IT managers need to find new ways to mitigate these ongoing threats. Consider investing in an adaptive DDoS protection approach that combines intelligent machine learning algorithms with dynamically updated, actionable DDoS threat intelligence.
When taking a more adaptive strategy, organizations can execute real-time traffic analysis using machine learning to inspect and analyze traffic with deeper granularity than was previously possible. These products can also detect zero-minute attacks and changes to attack vectors. Once an attack gets detected and classified, these type of products automatically understand the optimal mitigation methods that can be used to surgically and rapidly block the specific attack.
Furthermore, when we talk about creating adaptive DDoS defenses, we mean implementing technology and strategies that can identify changing attack vectors in the moment based on both software and human experience. For example, when one product detects an attack, the traffic can be analyzed instantly to offer additional countermeasures that were not possible with prior defense methodologies. This analysis gets continuously and automatically updated as characteristics of the attack traffic change. That level of deep analysis ultimately offers security teams with more rapid, effective mitigation methods than they have historically had at their disposal.
Unfortunately, bad actors will continue to evolve their tactics for pulling off new, automated DDoS attacks, which will also continue advancing in frequency and complexity. To stay one step ahead of these malicious exploits, IT organizations need to take a more pragmatic approach to their holistic mitigation of these evolving threats. That begins with an investment in intelligent DDoS mitigation systems that offer actionable, adaptable threat intelligence to automatically remediate issues before savvy attackers can pull off new exploits. While bad actors will continue to find new ways to attack, one fact remains: when defending against DDoS attacks, rapid, automatic detection can potentially stop an attack before it can impact service availability.
Gary Sockrider, director, security solutions, NETSCOUT
