Generative AI in cybersecurity: A comprehensive review of LLM applications and vulnerabilities
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Abstract
This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection, software engineering, design verification, cyber threat intelligence, malware detection, and phishing detection. We present an overview of LLM evolution and its current state, focusing on advancements in models such as GPT-4, GPT-3.5, Mixtral-8x7B, BERT, Falcon2, and LLaMA. Our analysis extends to LLM vulnerabilities, such as prompt injection, insecure output handling, data poisoning, DDoS attacks, and adversarial instructions. We delve into mitigation strategies to protect…
Citation impact
63
total citations
- FWCI
- 76.88
- Percentile
- 100%
- References
- 193
Citations per year
Authors
8Topics & keywords
Topics
Keywords
- Computer security
- Generative grammar
- Computer science
- Artificial intelligence
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