Selective Decryption of Encrypted Packets for DDoS Detection
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Solution Overview
Problem
DDOS attacks via encrypted connections are difficult to detect due to the computational complexity and time consumption of decrypting and re-encrypting data packets, which can slow down network traffic and hinder effective monitoring.
Innovation Solution
A system that selectively decrypts encrypted data packets based on network attack detection, using metric baselines to identify potential DDOS attacks without analyzing packet contents, by flagging suspicious devices and selectively decrypting packets associated with malicious activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all encrypted data packets are decrypted and re-encrypted for analysis, then network attack detection capability is improved, but network performance deteriorates due to computational overhead
Solution Approach 1:
The system applies different processing treatments to different data packets based on their characteristics. Only packets exhibiting attack patterns (identified through metric analysis) undergo decryption and detailed analysis, while normal packets are forwarded without decryption. This selective approach maintains detection capability for attacks while preserving network performance for legitimate traffic.
Solution Approach 2:
The detection process is segmented into two stages: first, metric baselines are established and monitored without decryption; second, only packets deviating from baselines are decrypted for detailed analysis. This segmentation reduces the volume of encrypted packets requiring computationally intensive decryption operations.
2Measurement precision
If encrypted data packets are decrypted for analysis, then detection accuracy is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary metric baseline establishment and monitoring on encrypted packets before decryption. By analyzing metrics such as packet size, inter-arrival time, and flow characteristics in encrypted form, the system pre-identifies suspicious packets, so that decryption is performed only on packets where it will actually contribute to detection accuracy.
Solution Approach 2:
Instead of decrypting all packets for full analysis, the system performs partial analysis by first examining encrypted packet metrics. Only when metrics indicate suspicious behavior does the system proceed to full decryption and content analysis, thus achieving sufficient detection accuracy for most cases while minimizing time consumption.
3Reliability
If metric baselines are established for all network devices, then DDOS attack detection capability is improved, but computational complexity increases
Solution Approach 1:
The system establishes a universal metric baseline framework that can be applied to all network devices using the same set of metrics (packet size, inter-arrival time, flow characteristics). This universal approach reduces computational complexity by using consistent measurement methods across devices rather than device-specific complex analysis, while maintaining detection capability through the multi-functional nature of the metrics.
Data Source
AI summary
Systems and methods for network traffic monitoring are provided. A system may monitor a first plurality of encrypted data packet exchanges between a server and a plurality of network devices, determine one or more metric baselines corresponding to a plurality of metric types for communication between the server and the plurality of network devices, monitor a second plurality of encrypted data packet exchanges between the server and a second plurality of network devices, identify a set of encrypted data packet exchanges from the second plurality of encrypted data packet exchanges each having a duration exceeding a first threshold, determine an exchange metric for each of the plurality of metric types, identify one or more encrypted data packet exchanges having at least one exchange metric exceeding a metric baseline, and apply a tag to one or more network devices of the second plurality of network devices.