all InfoSec news
Fingerprinting web servers through Transformer-encoded HTTP response headers
April 2, 2024, 7:11 p.m. | Patrick Darwinkel
cs.CR updates on arXiv.org arxiv.org
Abstract: We explored leveraging state-of-the-art deep learning, big data, and natural language processing to enhance the detection of vulnerable web server versions. Focusing on improving accuracy and specificity over rule-based systems, we conducted experiments by sending various ambiguous and non-standard HTTP requests to 4.77 million domains and capturing HTTP response status lines. We represented these status lines through training a BPE tokenizer and RoBERTa encoder for unsupervised masked language modeling. We then dimensionality reduced and concatenated …
accuracy art arxiv big big data cs.cr cs.lg cs.ni data deep learning detection domains fingerprinting headers http http requests language natural natural language natural language processing non requests response server servers standard state systems vulnerable web web server web servers
More from arxiv.org / cs.CR updates on arXiv.org
Jobs in InfoSec / Cybersecurity
SOC 2 Manager, Audit and Certification
@ Deloitte | US and CA Multiple Locations
Information Security Engineer - Vulnerability Management
@ Starling Bank | Southampton, England, United Kingdom
Manager Cybersecurity
@ Sia Partners | Rotterdam, Netherlands
Compliance Analyst
@ SiteMinder | Manila
Information System Security Engineer (ISSE)-Level 3, OS&CI Job #447
@ Allen Integrated Solutions | Chantilly, Virginia, United States
Enterprise Cyber Security Analyst – Advisory and Consulting
@ Ford Motor Company | Mexico City, MEX, Mexico