Information Security Based on LLM Approaches: A Review

TL;DR

This review explores how large language models (LLMs) are increasingly applied in information security to improve threat detection, vulnerability analysis, and cryptography, highlighting their advantages and current challenges.

Contribution

It systematically reviews recent applications of LLMs in information security and analyzes their technical foundations, advantages, and challenges for future development.

Findings

LLMs improve detection accuracy in security systems.

They help reduce false alarms in threat detection.

Current challenges include transparency and scene adaptability.

Abstract

Information security is facing increasingly severe challenges, and traditional protection means are difficult to cope with complex and changing threats. In recent years, as an emerging intelligent technology, large language models (LLMs) have shown a broad application prospect in the field of information security. In this paper, we focus on the key role of LLM in information security, systematically review its application progress in malicious behavior prediction, network threat analysis, system vulnerability detection, malicious code identification, and cryptographic algorithm optimization, and explore its potential in enhancing security protection performance. Based on neural networks and Transformer architecture, this paper analyzes the technical basis of large language models and their advantages in natural language processing tasks. It is shown that the introduction of large language modeling helps to improve the detection accuracy and reduce the false alarm rate of security systems. Finally, this paper summarizes the current application results and points out that it still faces challenges in model transparency, interpretability, and scene adaptability, among other issues. It is necessary to explore further the optimization of the model structure and the improvement of the generalization ability to realize a more intelligent and accurate information security protection system.