University Network Security Analysis Using Kali Linux:An Applied Study and a Naive Bayes Proposal

Abstract

The rapid shift toward digital transformation in higher education has exposed universities to escalating cybersecurity threats, particularly through wireless and cloud-based systems. This study conducts an applied security assessment of King Faisal University in Chad to identify technical and human vulnerabilities. Using Kali Linux tools (Aircrack-ng, Airodump-ng, Social Engineering Toolkit) combined with statistical analysis (ANOVA, Welch’s T-test, chi-square), the research tested 634 devices across four academic groups: faculty, computer engineering students, scientific disciplines, and humanities disciplines. Results showed that 51% of devices were compromised, with humanities students being the most vulnerable and faculty/computer engineering students the least. Findings revealed a statistically significant link between academic group and susceptibility, alongside weaknesses in network configurations. The study recommends strengthening institutional policies, enhancing awareness training, and upgrading technological infrastructure. Future research should integrate artificial intelligence techniques, such as Naive Bayes classifiers, for intelligent early detection systems. Despite its practical value, the study is limited to a single institution and a five-day observation period.