Akamai Technologies Launches Behavioral DDoS Engine Tool
/ 3 min read
Quick take - Akamai Technologies has launched the Behavioral DDoS Engine, a tool designed to enhance defenses against complex Distributed Denial of Service attacks by utilizing real-time adaptive capabilities and machine learning for traffic monitoring and threat identification.
Fast Facts
- Akamai Technologies has launched the Behavioral DDoS Engine to enhance defenses against complex DDoS attacks, addressing limitations of traditional methods.
- The engine utilizes real-time adaptive capabilities and machine learning to monitor traffic patterns, distinguishing between legitimate spikes and actual attacks.
- Over the past 18 months, more than 11 trillion Layer 7 DDoS attacks have been recorded, with a notable increase in the financial services sector due to geopolitical tensions.
- Key features include real-time traffic monitoring, tailored protection strategies, and three levels of risk tolerance: Strict, Moderate, and Conservative.
- The engine has demonstrated high performance, achieving a 99.95% detection rate during a DDoS attack on a ticketing website and is currently available to select customers, with broader access planned for 2025.
Akamai Technologies Introduces Behavioral DDoS Engine
Akamai Technologies has introduced a new tool, the Behavioral DDoS Engine, aimed at bolstering defenses against increasingly complex Distributed Denial of Service (DDoS) attacks.
Key Contributors
Aseem Ahmed, a Senior Manager of Product Management at Akamai, leads the development of security strategies for web applications and DDoS protection. Abdeslam Bella, a Principal Security Researcher on the Akamai Threat Research Team, plays a crucial role in contributing to the company’s App & API Protector security solutions.
Addressing DDoS Attack Challenges
The Behavioral DDoS Engine is designed to address the limitations of traditional DDoS defenses, which often rely on traffic throughput and static thresholds. Over the past 18 months, more than 11 trillion Layer 7 DDoS attacks have been recorded across various sectors, including high-tech industries, commerce, and social media. The financial services sector, particularly European banks, has experienced a notable increase in Layer 7 DDoS attacks, influenced by geopolitical tensions.
The Behavioral DDoS Engine is distinguished by its real-time adaptive capabilities. It continuously learns traffic patterns, allowing for real-time identification and mitigation of sophisticated DDoS threats. The engine employs machine learning to monitor anomalies in traffic, differentiating between legitimate spikes and actual DDoS attacks.
Advanced Features and Performance
Key features of the Behavioral DDoS Engine include real-time traffic monitoring and advanced algorithms for threat identification. The engine can tailor protection strategies to the specific needs of each website or API, analyzing traffic trends across multiple dimensions, such as country of origin, client TLS patterns, and network fingerprints. It generates baseline traffic reports that enhance user confidence and provide insights into protection measures.
To accommodate varying levels of risk tolerance, the engine offers three distinct levels of protection: Strict, Moderate, and Conservative. Its multidimensional view of traffic, coupled with historical attack data, allows for effective DDoS attack identification and mitigation. The mitigation engine leverages intelligence from both the baseline generator and threat signals to counteract DDoS attacks effectively.
Akamai’s Behavioral DDoS Engine has demonstrated impressive performance in case studies, achieving a 99.95% detection rate during a DDoS attack on a ticketing website during the Olympic Games in Paris, and a 99.50% detection and mitigation accuracy during an attack on an e-commerce homepage. The Behavioral DDoS Engine is positioned as a significant advancement in DDoS defense, enhancing detection accuracy while reducing the need for manual intervention. Currently, the engine is available to a select group of customers, with plans for platform-wide access expected in 2025.
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