Feb. 9, 2024, 5:10 a.m. | Mohamed Amine Ferrag Mthandazo Ndhlovu Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Thierry Lestable

cs.CR updates on arXiv.org arxiv.org

The field of Natural Language Processing (NLP) is currently undergoing a revolutionary transformation driven by the power of pre-trained Large Language Models (LLMs) based on groundbreaking Transformer architectures. As the frequency and diversity of cybersecurity attacks continue to rise, the importance of incident detection has significantly increased. IoT devices are expanding rapidly, resulting in a growing need for efficient techniques to autonomously identify network-based attacks in IoT networks with both high precision and minimal computational requirements. This paper presents SecurityBERT, …

architectures attacks bert continue cs.ai cs.cr cyber cybersecurity cybersecurity attacks cyber threat cyber threat detection detection devices diversity iiot incident incident detection iot language language models large llms natural natural language natural language processing nlp power privacy threat threat detection transformation

Information Security Engineers

@ D. E. Shaw Research | New York City

Technology Security Analyst

@ Halton Region | Oakville, Ontario, Canada

Senior Cyber Security Analyst

@ Valley Water | San Jose, CA

Senior - Penetration Tester

@ Deloitte | Madrid, España

Associate Cyber Incident Responder

@ Highmark Health | PA, Working at Home - Pennsylvania

Senior Insider Threat Analyst

@ IT Concepts Inc. | Woodlawn, Maryland, United States