Virtual Environment Software Bug Detection Training

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Solution Overview

Problem

Computing systems are vulnerable to malicious manipulation, necessitating the development of software bug detection systems that can train users and systems to dynamically identify and remediate vulnerabilities.

Innovation Solution

A method and system where an administrative computing system deploys virtual computing resources with predefined software bugs to client computing systems, allowing users or AI to evaluate, correct, and exploit these bugs, with verification leading to score increases and reporting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If computing systems use traditional security measures, then system security is maintained, but the systems remain vulnerable to malicious manipulation and exploitation

Engineering Contradiction:

Improvesystem securityVSAvoidvulnerability to malicious manipulation

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary actions by deploying simulated software bugs and vulnerabilities into virtual computing environments before real attacks occur. These pre-configured vulnerabilities serve as training data and detection targets, allowing the system to learn and improve security detection capabilities in advance of actual threats.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of real-world vulnerabilities by implementing simulated software bugs that replicate actual attack vectors. These copied vulnerabilities are deployed in virtual environments to train detection algorithms without requiring actual compromised systems, enabling safe and repeatable security training.

Inventive Principle:

Principle #26Copying

2Measurement precision

If the system deploys simulated software bugs to train detection systems, then the ability to identify vulnerabilities improves, but the complexity of the system increases

Engineering Contradiction:

Improvevulnerability detection accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the complex security training task into distinct components: virtual computing environments, simulated software bugs, detection algorithms, and verification mechanisms. Each component operates independently but contributes to the overall vulnerability detection capability, making the system more manageable and scalable.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary layer of virtual computing environments that mediate between real-world vulnerabilities and detection algorithms. This intermediary layer isolates the complexity of actual security threats while providing controlled access to detection systems, simplifying the training process.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If users and systems are trained to dynamically identify bugs, then security response capability improves, but the time required for training and verification increases

Engineering Contradiction:

Improvesecurity response capabilityVSAvoidtraining and verification time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system enables continuous security training and detection practice by deploying simulated bugs that can be repeatedly identified and corrected. The virtual environment allows uninterrupted training activities without affecting production systems, maintaining continuous improvement of detection capabilities.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The system implements self-service mechanisms where the virtual computing environments automatically verify bug identifications and provide feedback without requiring constant human intervention. This automated verification process reduces the time investment needed for manual checking while maintaining training effectiveness.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12045160B2Systems and methods for training systems to detect software bugs

Publication Date: 2024.07.23 ARIES SECURITY LLC

AI summary

A method is disclosed and includes receiving, using a first client computing system, an instance from an administrative computing system. The instance includes a partition of computing resources of the administrative computing system. The partition of computing resources includes a virtual processor and first machine-readable instructions. The first machine-readable instructions include a first predefined software bug. The method includes executing, using the virtual processor, the first machine-readable instructions. Executing the first machine-readable instructions includes receiving, using the virtual processor, a first input indicating an identification of the first predefined software bug of the first machine-readable instructions. Executing the first machine-readable instructions includes transmitting, using the virtual processor, a first signal associated with the first input to the administrative computing system, wherein the first signal causes the administrative computing system to generate a score associated with the first client computing system in response to verification by the administrative computing system.