Adaptive Incident Logging for High-Volume Cyber Threat Flows
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Solution Overview
Problem
Existing cyber defense systems are overwhelmed by large volumes of logs generated during cyber threats, leading to resource exhaustion and compromising network security, akin to a denial-of-service attack.
Innovation Solution
Implement adaptive logging methods that generate a single incident log for multiple flows and packets, reducing resource consumption while maintaining informational value, using packet-filtering devices with auto-log and auto-capture directives to select optimal logging modes based on threat environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If packet filtering rules log each packet individually, then detailed information for cyber analysis is captured, but network resources are overwhelmed and system performance degrades
Solution Approach 1:
The patent merges multiple individual packet logs into a single flow log by aggregating packets that share the same 5-tuple (source IP, destination IP, source port, destination port, protocol). This consolidation reduces the volume of log data from millions of individual packet records to a manageable set of flow-level records, directly resolving the contradiction between capturing detailed information and consuming network resources.
Solution Approach 2:
The patent creates a simplified representation (copy) of packet flow information at the flow level rather than copying every individual packet. The flow log contains summarized attributes such as total packet count, total bytes transferred, and timing information, which preserve the essential cyber analysis value while dramatically reducing data volume and resource consumption.
2Productivity
If flow logging is implemented to reduce packet-level log volume, then resource consumption decreases, but detailed packet information is lost
Solution Approach 1:
The patent applies different levels of detail to different aspects of the log data. At the flow level, it captures aggregated statistics (packet counts, byte totals, duration) that provide high-level overview information, while preserving individual packet details only when specifically needed for analysis. This localized quality approach allows the system to reduce overall resource consumption while maintaining the ability to access detailed information when required.
3Reliability
If adaptive logging modes are implemented to respond to attack patterns, then cyber defense effectiveness improves, but system complexity increases
Solution Approach 1:
The patent implements dynamic logging behavior that automatically adjusts based on detected attack patterns and network conditions. The system transitions between different logging modes (packet-level logging during suspected attacks, flow-level logging during normal operations) based on real-time analysis of network traffic characteristics, thereby improving cyber defense effectiveness while managing system complexity through automated adaptation.
Solution Approach 2:
The patent incorporates feedback mechanisms where the logging system monitors network traffic patterns and adjusts its logging behavior based on this feedback. When anomalies or attack patterns are detected, the system modifies its logging strategy in real-time, creating a closed-loop system that improves cyber defense effectiveness while containing complexity through rule-based decision logic.
Data Source
AI summary
A packet-filtering network appliance such as a threat intelligence gateway (TIG) protects TCP/IP networks from Internet threats by enforcing certain policies on in-transit packets that are crossing network boundaries. The policies are composed of packet filtering rules derived from cyber threat intelligence (CTI). Logs of rule-matching packets and their associated flows are sent to cyberanalysis applications located at security operations centers (SOCs) and operated by cyberanalysts. Some cyber threats/attacks, or incidents, are composed of many different flows occurring at a very high rate, which generates a flood of logs that may overwhelm computer, storage, network, and cyberanalysis resources, thereby compromising cyber defenses. The present disclosure describes incident logging, in which a single incident log efficiently incorporates the logs of the many flows that comprise the incident, thereby potentially reducing resource consumption while improving the informational/cyberanalytical value of the incident log for cyberanalysis when compared to the component flow logs. Incident logging vs. flow logging can be automatically and adaptively switched on or off depending on the combination of resource consumption and informational/cyberanalytical value.