Honeypot Anomaly Detection for Zero-Day Threat Mitigation
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Solution Overview
Problem
Current computer security systems, including antivirus software and intrusion prevention systems, are inadequate in detecting and preventing 'zero-day' attacks and are limited in handling unknown threats, as they rely on pre-existing patches and signatures, and existing honeypots and anomaly detection systems suffer from high false positive and false negative rates, making them ineffective against certain types of attacks.
Innovation Solution
Implementing a system that combines an anomaly detection component with a shadow honeypot that shares state information with the protected application, allowing for the processing of anomalous traffic by the honeypot instead of the main application, and using feedback to tune the anomaly detection component and filter, thereby minimizing false negatives and validating legitimate traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional antivirus software and firewalls are used, then protection against known threats is provided, but they are ineffective against zero-day attacks and new threats
Solution Approach 1:
The system performs preliminary actions by deploying honeypots and anomaly detection mechanisms before actual attacks occur. These components are pre-configured to detect and respond to zero-day threats, allowing the system to identify and neutralize new attacks before they can compromise the protected application.
Solution Approach 2:
The patent introduces intermediary components (honeypots and anomaly detection systems) that act as mediators between external threats and the protected application. These intermediaries absorb and analyze attack traffic, providing an additional layer of defense that doesn't rely on pre-existing security signatures or rules.
2Adaptability or versatility
If honeypots are used to detect attacks, then zero-day attacks can be detected, but legitimate traffic may be misclassified and processing speed decreases
Solution Approach 1:
The patent merges multiple detection approaches by combining honeypot-based anomaly detection with traditional security measures. This hybrid approach allows the system to leverage the strengths of each method: honeypots for detecting zero-day threats and traditional systems for handling known threats, thereby reducing false positives while maintaining detection effectiveness.
Solution Approach 2:
The system dynamically adjusts its detection sensitivity and traffic routing based on learned patterns and current threat levels. By making the detection system adaptive rather than static, it can reduce false positives over time while maintaining high detection rates for actual threats.
3Adaptability or versatility
If anomaly detection systems are tuned to detect more attacks, then detection coverage increases, but false positive rate increases and legitimate traffic is affected
Solution Approach 1:
The patent segments traffic handling by directing suspicious traffic to honeypots for analysis while allowing clearly legitimate traffic to pass through the protected application unchanged. This segmentation enables comprehensive anomaly detection for potential threats while minimizing impact on legitimate traffic flow.
Solution Approach 2:
The system creates copies of suspicious traffic and routes them to honeypots for analysis, while the original traffic continues to be processed by the protected application. This copying approach allows thorough inspection of potential threats without disrupting legitimate operations.
Data Source
AI summary
In accordance with some embodiments, systems and methods that protect an application from attacks are provided. In some embodiments, traffic from a communication network is received by an anomaly detection component. The anomaly detection component monitors the received traffic and routes the traffic either to the protected application or to a honeypot, where the honeypot shares all state information with the application. If the received traffic is routed to the honeypot, the honeypot monitors the traffic for an attack. If an attack occurs, the honeypot repairs the protected application (e.g., discarding any state changes incurred from the attack, reverting to previously saved state information, etc.).