AI-Generated Redundant Code for Malicious-Exploit Resilience
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Solution Overview
Problem
Existing software redundancy methods, such as identical copies in software or hardware, are insufficient to protect against malicious attacks or faults, as they do not address vulnerabilities introduced unintentionally but exploited maliciously, leading to potential system failures.
Innovation Solution
A method and system that generates redundant code using artificial intelligence to create two different software versions with the same functionality, enabling robust software applications by switching to a fault-free version upon detection of vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If identical copies of software are used for redundancy, then system reliability is improved, but vulnerability to malicious attacks worsens because the same vulnerabilities exist in both copies
Solution Approach 1:
The patent applies asymmetry by generating two different software versions (first and second software programs) that perform the same function but have different code structures. This asymmetric approach ensures that vulnerabilities present in one version are not necessarily present in the other, thereby protecting the system from malicious attacks that target specific code patterns while maintaining functional redundancy for reliability.
2Object-affected harmful factors
If AI-generated redundant code is used, then protection against malicious exploits is improved, but system complexity increases due to managing multiple software versions
Solution Approach 1:
The patent uses copying by creating a second software program that replicates the functionality of the first software program but with different code generated by an AI engine. This copying approach provides protection against malicious exploits while managing complexity through automated generation and verification processes, where the redundant copy is systematically created and tested rather than manually developed.
Solution Approach 2:
The system applies self-service by automatically generating the second software version using an AI engine, automatically verifying its functionality through a test suite, and automatically switching between versions based on detected faults. This automation reduces the manual complexity of managing multiple software versions while maintaining the protective redundancy against malicious exploits.
3Ease of manufacture
If traditional redundancy methods are used, then development costs are reduced, but effectiveness against safety events and malicious attacks worsens
Solution Approach 1:
The patent applies parameter changes by transforming the redundancy approach from identical copies to AI-generated different versions. This change in the fundamental parameter of code similarity improves effectiveness against both safety events and malicious attacks while maintaining cost-efficiency through automated AI generation and testing, rather than requiring extensive manual development of redundant systems.
Data Source
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AI summary
A method for generating redundant code includes receiving a first software program and providing, to an artificial intelligence engine, the first software program configured to perform a function. The method also receiving, from the artificial intelligence engine, a second software program configured to perform the function. The method also includes, in response to verifying the function of the second software program executing at least one of the code of the first software program and the code associated with the second software program to cause the function to be performed. The method also includes, in response to detecting a fault, disabling execution of one of the first software program and the second software program, and executing the other of the first software program and the second software program to cause the function to be performed.