Distributed Honey Pot Pattern Detection for Intrusion Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Intrusion detection systems (IDS) face challenges in detecting novel attacks and keeping up with the multitude of attack variations, as they rely on predefined patterns that need frequent updates and may not catch the latest threats until new signatures are released.
Innovation Solution
A distributed honey pot system collects and analyzes network traffic information to detect patterns indicative of malicious behavior, generating response data to automatically or manually respond to potential threats, thereby reducing the reliance on predefined attack patterns and improving detection of novel attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If predefined attack patterns are used in IDS, then detection of known attacks is improved, but detection of novel attacks deteriorates
Solution Approach 1:
The system performs preliminary actions by deploying honey pots before attacks occur and continuously collecting traffic information in advance. This allows the system to build a database of attack patterns proactively, enabling detection of both known and novel attacks without waiting for signature updates
Solution Approach 2:
The system implements feedback by continuously analyzing traffic information from distributed honey pots and using detected patterns to improve future detections. The pattern detection results feed back into the system to enhance its ability to identify both known and novel attacks dynamically
2Reliability
If predefined patterns are frequently updated, then detection of latest threats is improved, but system complexity and maintenance difficulty worsen
Solution Approach 1:
The system performs self-service by automatically detecting patterns from collected traffic information without requiring manual intervention. The automated pattern detection and response data generation eliminate the need for frequent manual signature updates, reducing system complexity while maintaining detection effectiveness
Solution Approach 2:
The system replaces the mechanical process of manual pattern creation, testing, and deployment with an automated information processing system. Traffic information is automatically analyzed and patterns are generated through computation rather than human effort, significantly reducing maintenance complexity
3Measurement precision
If distributed honey pot system is deployed, then detection capability is improved, but system complexity increases
Solution Approach 1:
The system merges information from multiple distributed honey pots into a unified analysis framework. By combining traffic information from various locations and applying centralized pattern detection, the system achieves high detection accuracy while managing complexity through integration rather than distributed independent analysis
Data Source
AI summary
A honey pot system, method and computer program product are provided. In use, information is collected which relates to network traffic targeting a plurality of computers associated with a distributed honey pot system. Next, a pattern is detected among the information collected from the distributed honey pot system. To this end, response data is generated, if the pattern is detected.