Exploring Personalized Personnel Protection within Cybersecurity

Abstract

Due to their substantial cross-platform exposure, high-profile persons are disproportionately at danger as cyber threats grow across linked digital ecosystems. Most prior research has focused on discrete platform vulnerabilities; however, the ways in which interconnections across services create compound socio-technical hazards have received less attention. By taking a socio-technical systems approach, this study highlights a major flaw in current methods that treat users as a homogeneous population, despite notable differences in exposure and behaviour. The study identifies recurring vulnerability patterns and illustrates how coordinated adversarial activity leverages digital interdependencies to cause financial, reputational, and physical harm through a cross-sector analysis of five high-demand service categories, ranging from remote healthcare to on-demand gig services. It identifies recurring structural vulnerability configurations across sectors, demonstrating that risk stems from shared choices rather than platform specifics. This paper contributes a cross-platform vulnerability map, a socio-technical risk model for high-visibility individuals, and a unified framework linking adversarial behavior to privacy erosion across interconnected services, offering practical insights for developing targeted cybersecurity strategies. Findings show how attackers exploit digital interdependence to achieve blended online compromise, financial loss, reputational harm, and physical danger. The study concludes by proposing a paradigm shift to personalized, privacy-centric, multi-layered cybersecurity capable of safeguarding both high-profile and everyday users emphasizing the importance of adapting security measures to individual user needs while prioritizing the protection of sensitive information. This study employs a socio-technical systems framework, acknowledging that cybersecurity risk arises from the interplay of human behaviour, platform structures, and data flows, rather than from isolated technical vulnerabilities.