Autonomous Agent DDoS Mitigation Across Multi-Cloud Application Gateways
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems fail to effectively detect and mitigate application-layer Distributed Denial of Service (DDoS) attacks on a shared infrastructure, particularly in environments where existing systems rely on manual intervention and are prone to errors and are prone to errors and are prone to errors and are prone to errors and are prone to errors and are prone to errors and are prone to errors and are prone to errors.
Innovation Solution
Implementing an automated system for detecting and mitigating the application-layer DDoS attacks, utilizing an automated system for detecting and mitigating the application-layer DDoS attacks, utilizing an automated system for detecting and mitigating the application-layer DDoS attacks, utilizing an automated system for detecting and mitigating the application-layer DDoS attacks, utilizing an automated system for detecting and mitigating the application-layer DDoS attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used for detecting and mitigating DDoS attacks, then system complexity is reduced, but detection accuracy and response effectiveness deteriorate
Solution Approach 1:
The system employs autonomous agents that automatically detect, analyze, and mitigate DDoS attacks without requiring manual human intervention. These agents continuously monitor traffic patterns, identify attack signatures, and execute mitigation strategies autonomously, enabling the system to serve itself in detecting and responding to threats while maintaining high detection accuracy
Solution Approach 2:
The patent replaces manual mechanical intervention with automated electronic systems including machine learning models, pattern recognition algorithms, and automated response mechanisms. This substitution transforms the detection and mitigation process from human-operated to system-autonomous, improving both accuracy and speed while managing complexity through structured automation
2Productivity
If automated systems are implemented for DDoS detection and mitigation, then response speed and accuracy improve, but system complexity increases
Solution Approach 1:
The automated system is divided into distinct functional modules including traffic analysis components, attack detection agents, mitigation execution engines, and logging systems. Each segment performs a specific function independently, allowing the system to achieve high response speed through specialized processing while managing overall complexity through modular architecture
Solution Approach 2:
The system performs preliminary actions by pre-configuring mitigation strategies, pre-training detection models, and establishing response protocols before attacks occur. This preparation enables rapid automated response when attacks are detected, improving productivity while the complexity is managed through advance planning and structured deployment
3Reliability
If manual intervention is used for DDoS mitigation, then automation cost is reduced, but mitigation effectiveness deteriorates
Solution Approach 1:
The system implements continuous feedback loops where autonomous agents monitor the effectiveness of mitigation actions in real-time, adjust strategies based on attack evolution, and learn from past incidents. This feedback mechanism ensures high mitigation effectiveness by dynamically adapting to changing threat patterns while maintaining appropriate automation levels
Solution Approach 2:
The automated mitigation system dynamically adjusts its behavior based on attack characteristics, traffic patterns, and system state. Rather than following rigid manual protocols, the system adapts its response strategies in real-time, improving mitigation effectiveness while managing automation complexity through flexible, context-aware decision-making
4Loss of time
If automated detection and mitigation systems are deployed, then response time is reduced, but system resource consumption increases
Solution Approach 1:
The system applies partial automation selectively to critical detection and mitigation functions rather than automating all system operations. By focusing automated resources on high-value security functions and leaving routine operations manual or semi-automated, the system achieves reduced response time for security incidents while controlling overall resource consumption
Data Source
AI summary
A computing services environment may include application gateways receiving application-layer request messages from various sources. The computing services environment may also include an autonomous agent platform configured to instantiate and execute an autonomous agent to evaluate network traffic associated with a portion of the computing services environment. The computing services environment may also include an orchestration engine configured to determine one or more mitigation policies corresponding with one or more of the application gateways based on identification of the application-layer distributed denial of service attack by the autonomous agent. The computing services environment may also include application-layer web application firewalls corresponding to the plurality of application gateways and implementing the one or more mitigation policies to prevent a subset of subsequent application-layer request messages from the subset of the sources from reaching one or more components of the computing services environment.