Improving network resilience against DDoS attacks: A fuzzy TOPSIS-based quantitative assessment approach.

Security in data transmission is becoming problematic due to the internet's explosive growth as well as the spread of social media and digital advertising platforms, which have produced enormous volumes of data every day. In order to safeguard sensitive data, network security is becoming more and more important as technology is adopted. Effective information security measures are needed to protect against a variety of dangers, given the expanding number of users. A key factor in improving security is network security attributes, which include message encryption, password breaking, safeguarding wireless networks, and finding security holes. This paper adopts the Multi-Criteria Decision Making (MCDM) approach, utilising a fuzzy TOPSIS-based method, with the objective of systematically evaluating resilience in network security, especially against DDoS attacks. The research assesses different security attributes and vulnerabilities to offer actionable insights on how best to strengthen organizational cybersecurity frameworks. The methodology encompasses conducting network security audits to identify vulnerabilities that could compromise commercial operations or expose sensitive data. The findings provide critical insights that can inform targeted actions to address these vulnerabilities and enhance resource protection. The results indicate that network N6 is the most secure under DDoS attacks, followed by networks N1, N5, N3, N4, and N2. This research is significant as it aids strategic decision-making, strengthens network defenses, and enhances overall cybersecurity resilience in an era of evolving cyber threats. By addressing the complexities of network security assessments, this study makes a crucial contribution to the ongoing efforts of organisations to safeguard their data, employees, and customer information from sophisticated cyber threats.