Network Traffic Management System for DDoS Attack Prevention
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Solution Overview
Problem
Existing network traffic management systems are inadequate in preventing recurring distributed denial of service (DDoS) attacks as they only temporarily drop malicious devices from the network, allowing them to reconnect and resume attacks.
Innovation Solution
A network traffic management system that analyzes traffic data based on predefined rules to identify current or predicted attacks, enforces policy changes on client devices to prevent such attacks by throttling or rerouting traffic, and adapts network infrastructure to block suspicious activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If malicious devices are dropped from the network to stop DDoS attacks, then the attack is temporarily stopped, but the malicious devices can reconnect and resume the attack
Solution Approach 1:
The system performs preliminary actions by analyzing network traffic patterns before attacks fully materialize, identifying potential malicious devices through behavioral analysis and establishing policy changes in advance. This allows the system to prevent attacks before they occur rather than merely reacting to them after detection.
Solution Approach 2:
The system implements dynamic network policies that automatically adjust based on real-time traffic analysis. Policy changes are enforced dynamically on client devices, allowing the network to adapt its security measures continuously rather than relying on static, temporary drop actions. This dynamic approach ensures long-term protection by evolving with threat patterns.
2Ease of operation
If network traffic devices use simple drop actions to stop attacks, then the implementation is simple and fast, but the protection is not robust and allows recurring attacks
Solution Approach 1:
The system enables client devices to self-regulate their network behavior through automatically enforced policy changes. Rather than requiring manual intervention or simple centralized drop actions, the system empowers individual devices to adjust their own traffic patterns based on analyzed attack patterns, creating a self-service security mechanism that is both simple to operate and robust in protection.
Solution Approach 2:
The system implements continuous feedback loops where network traffic is constantly analyzed, policy effectiveness is monitored, and adjustments are automatically made. This feedback mechanism transforms simple drop actions into a sophisticated, adaptive system that learns from each attack attempt and improves its response, achieving both operational simplicity and protection robustness.
Data Source
AI summary
A method, non-transitory computer readable medium, and device for analyzing network traffic and enforcing network policies includes analyzing network traffic data based on one or more network traffic rules. An attack on the network such as a current or predicted attack is determined based on the analysis. Next, one or more policy changes to a plurality of existing network policies are identified when the current or predicted attack on the network is determined to be present. The identified one or more policy changes are enforced on one or more client computing devices causing the determined current or the predicted attack on the network.