Detection of Vulnerabilities in Smart Buildings Using the Shodan Tool

Abstract

Smart buildings, integral components of modern urban landscapes, are confronted with diverse vulnerabilities that jeopardize system robustness, cybersecurity, data confidentiality, and the well-being of the occupants. This work aimed to identify and evaluate vulnerabilities specific to smart buildings, introducing an innovative assessment approach leveraging the Shodan tool. The analysis comprised three stages: information collection, result extraction using Shodan, and vulnerability identification, culminating in a comprehensive evaluation. This study pioneers the use of Shodan for smart building vulnerability detection, together with databases and associated nomenclature, to serve as a robust foundational tutorial for future research. The findings yielded a meticulous analysis of primary security risks inherent in building systems, advocating for implementing targeted measures to mitigate potential impacts. Additionally, this study proposes an evaluation methodology encompassing metrics to gauge the effect of vulnerabilities on integrity, availability, and scope. By addressing insecure configurations, deployment inadequacies, and suboptimal cybersecurity practices, this framework fortifies smart buildings against potential threats. This study’s originality lies in its Shodan-centric framework, revolutionizing the approach to smart building applications and vulnerability detection. This research contributes to the field by identifying critical vulnerabilities and proposing effective mitigation strategies, thereby elevating the overall security and safety of interconnected smart spaces.