Automated Software Fault Recovery via Byte Replacement
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Solution Overview
Problem
Existing software systems lack an efficient method to automatically detect and rectify faults or failures, such as malware infections, during runtime without interrupting the software's operation.
Innovation Solution
A method that continuously monitors the software's behavior against a stored model, detects anomalies, performs root cause analysis, and automatically replaces memory values to restore acceptable behavior, using predictive analytics to predict the success of these corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software systems implement traditional fault detection and correction methods, then fault detection capability is improved, but software operation is interrupted and productivity decreases
Solution Approach 1:
The system performs preliminary actions by predicting future software states and identifying potential faults before they occur. The predictive analytics module analyzes current and historical software behavior to forecast future states, enabling proactive fault detection and correction while the software continues to run normally, thus maintaining productivity while improving reliability
Solution Approach 2:
The software system performs self-diagnosis and self-correction through automated fault detection and remediation. The system monitors its own behavior, compares it against predicted states, and automatically corrects deviations without human intervention or software interruption, allowing the system to service itself while maintaining continuous operation
2Measurement precision
If software systems implement comprehensive monitoring and analysis, then fault detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system creates a virtual model (copy) of the software's expected behavior through predictive analytics. Instead of implementing complex physical monitoring infrastructure, the system generates predicted state representations that can be compared against actual software behavior, achieving high detection accuracy through informational copying rather than physical complexity
Solution Approach 2:
The predictive analytics module serves as an intermediary between the software execution and the fault detection mechanism. It translates complex software behavior into predicted state representations that are easier to analyze and compare, simplifying the detection process while maintaining high accuracy through the intermediary's analytical capabilities
3Reliability
If software systems perform real-time fault correction, then reliability is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary computational analysis to predict future software states and identify potential faults before they manifest. By preparing predictions and correction strategies in advance based on current and historical data, the system reduces the time needed for actual fault correction, maintaining high reliability while minimizing processing time losses
Solution Approach 2:
The system dynamically adjusts its monitoring and analysis intensity based on software behavior patterns. The predictive analytics module continuously adapts its predictions based on changing software states, optimizing the balance between detection accuracy and processing time by focusing computational resources on high-risk periods or anomalous behaviors rather than uniform continuous analysis
Data Source
AI summary
An exemplary method provides for automatically curing a detected behavior anomaly in executing target software during the continuing execution of the target software. Ranges of parameters of acceptable behaviors are stored. One behavior is detected that is outside the range of parameters for acceptable behavior for the corresponding behavior. A probability of success is predicted for restoring the corresponding behavior to acceptable behavior. First bytes associated with the behavior anomaly are replaced with the other bytes upon the predicted probability of success exceeding a predetermined success threshold, thereby automatically implementing a likely cure of a detected anomaly in the target software during the continuous execution of the target software.