The primary function of Akamai Adaptive Security Engine (ASE) is to provide real-time, always-current defenses against application-layer attacks for web applications and APIs. It uses advanced analytics and automation to identify and mitigate threats with high precision and minimal operational overhead.
Key Takeaways
- Akamai Adaptive Security Engine (ASE) provides real-time, always-current defenses against application-layer attacks.
- ASE uses AI and automation to identify and mitigate attacks with high precision and minimal operational overhead.
- ASE is built for trust, with algorithms compliant with strict regulatory frameworks.
- ASE has been recognized as a leader in cloud WAAP solutions by third-party testing and analyst reports.
- ASE reduces false positives and alert fatigue, allowing security teams to focus on critical tasks.
Akamai Products Mentioned
Frequently Asked Questions (FAQ)
ASE differs from traditional WAF solutions by using a multidimensional threat scoring model that evaluates global threat intelligence, application-specific traffic behavior, and per-request data. This approach allows ASE to adapt to new and evolving attack types, minimize false positives, and provide context-aware protection, unlike static rulesets used by traditional WAFs.
Adaptive Intelligence is the decision-making layer within ASE that analyzes each request and adjusts protections dynamically. It combines flexible threat scoring, behavioral signals, and anomaly detection to evaluate traffic in context, fine-tune security responses in real time, and minimize false positives, making ASE highly effective against sophisticated attacks.
The Penalty Box is an important feature of ASE because it helps contain active attack sessions by automatically blocking further requests from the same IP after a "Deny" action is triggered. This increases the cost for attackers and reduces their ability to probe and evade, providing a two-pronged defense of precision blocking and active attack session disruption.
ASE helps organizations reduce false positives and alert fatigue by making adaptive, context-aware decisions per request. It uses an AI-powered automated false-positive detection system and evaluates traffic through a multi-signal lens, which significantly improves precision and reduces the need for manual tuning and exception management.
Balanced Accuracy is a benchmark that reflects how well ASE maintains high security without overblocking. It is the average of true positive and true negative rates, and ASE consistently scores among the highest for this metric in internal and third-party testing, ensuring confident protection without collateral damage.
ASE's global visibility, which includes insights from more than 1.3 billion client interactions daily, contributes to its effectiveness by providing a comprehensive understanding of traffic patterns and threats. This data is used to detect anomalies, refine protections, and inform real-time decision-making, making ASE more adept at identifying and mitigating evasive and targeted attacks.
Using ASE in Automatic mode provides several business benefits, including reduced false positives and alert fatigue, simplified operations with automatic updates, consistent and secure user experiences, and the ability to scale securely without increasing security headcount. These features help organizations maintain robust protection while minimizing operational overhead.