2/5/2025 | 4:10 PM - 5:10 PM | Harbour A

AI-based vulnerability scanners: A cross-sectional survey analysis

Author(s)

Sam Chemparathy | SRH Berlin University of Applied Sciences
Navaneeth Shivananjappa | SRH Berlin University of Applied Sciences
Reiner Creutzburg | SRH Berlin University of Applied Sciences

Abstract

One major innovation in improving organizations' security measures is the adoption of AI-based vulnerability scanners within the cybersecurity space. The paper analyzes cross-sectional survey research identifying factors that influence the acceptance and use of such advanced tools among cybersecurity professionals. The primary method of gathering data was a structured survey questionnaire that used Likert-scale questions to quantify the participants' opinions objectively. It contained 20 questions based on established models, including TAM, UTAUT, and IDT. In this research, the total number of people who responded to the survey was 49, comprising cybersecurity professionals working in various industry domains. This instrument has measured perceived usefulness, ease of use, performance expectancy, effort expectancy, social influence, facilitating conditions, and the stages of adoption, including awareness, interest, evaluation, trial, and adoption. Our results provide insight into factors that drive or hinder the adoption of AI-based vulnerability scanners, focusing on the significant role of perceived benefits and organizational support. The present paper offers valuable implications for practitioners and researchers who aim to foster AI-driven security solutions within organizational contexts.