PromSec: An AI Algorithm for Prompt Optimization for Secure and Functioning Code Generation Using LLM
Practical Solutions and Value
Software development has seen significant benefits with Large Language Models (LLMs) for producing high-quality source code, reducing time and cost. However, LLMs often generate code with security flaws due to unsafe coding techniques in training data.
To address this, PromSec has been introduced to refine LLM instructions for secure code generation. It combines Vulnerability Removal using a generative adversarial graph neural network (gGAN) to fix security flaws, and an Interactive Loop for iterative feedback between gGAN and LLM to enhance code security and functionality.
PromSec optimizes code generation by reducing LLM inferences and enhancing code security. It has been tested with Python and Java datasets, showing significant improvements in security while maintaining functionality, reducing operational expenses, and providing generalizability across different programming languages.
PromSec is a breakthrough in secure code generation using LLMs, enhancing reliability, scalability, and affordability for large-scale software development. It ensures secure integration of LLMs into practical coding techniques, expanding their application across various industries.
AI Implementation Recommendations
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