all InfoSec news
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
Feb. 28, 2024, 5:11 a.m. | Tosin Ige, Christopher Kiekintveld, Aritran Piplai
cs.CR updates on arXiv.org arxiv.org
Abstract: To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there are different types of …
art arxiv attack attackers commit computers cs.ai cs.cr cs.lg cyber cyber-attack cybercrime detection information investigation machine machine learning real security state survey system systems vulnerabilities
More from arxiv.org / cs.CR updates on arXiv.org
Jobs in InfoSec / Cybersecurity
Security Engineer
@ SNC-Lavalin | GB.Bristol.The Hub
Application Security Engineer
@ Virtru | Remote
SC2024-003563 Firewall Coordinator (NS) - TUE 21 May
@ EMW, Inc. | Mons, Wallonia, Belgium
Senior Application Security Engineer
@ Fortis Games | Remote - Canada
DevSecOps Manager
@ Philips | Bengaluru – Embassy Business Hub
Information System Security Manager (ISSM)
@ ARA | Raleigh, North Carolina, United States