The coronavirus pandemic led to an unprecedented crisis affecting all aspects of the concurrent reality. Its consequences vary from political and societal to technical and economic. These side effects provided fertile ground for a noticeable cyber-crime increase targeting critical infrastructures and, more specifically, the health sector; the domain suffering the most during the pandemic. This paper aims to assess the cybersecurity culture readiness of hospitals’ workforce during the COVID-19 crisis. Towards that end, a cybersecurity awareness webinar was held in December 2020 targeting Greek Healthcare Institutions. Concepts of cybersecurity policies, standards, best practices, and solutions were addressed. Its effectiveness was evaluated via a two-step procedure. Firstly, an anonymous questionnaire was distributed at the end of the webinar and voluntarily answered by attendees to assess the comprehension level of the presented cybersecurity aspects. Secondly, a post-evaluation phishing campaign was conducted approximately four months after the webinar, addressing non-medical employees. The main goal was to identify security awareness weaknesses and assist in drafting targeted assessment campaigns specifically tailored to the health domain needs. This paper analyses in detail the results of the aforementioned approaches while also outlining the lessons learned along with the future scientific routes deriving from this research.
Recent studies report that cybersecurity breaches noticed in hospitals are associated with low levels of personnel’s cybersecurity awareness. This work aims to assess the cybersecurity culture in healthcare institutions from middle- to low-income EU countries. The evaluation process was designed and performed via anonymous online surveys targeting individually ICT (internet and communication technology) departments and healthcare professionals. The study was conducted in 2019 for a health region in Greece, with a significant number of hospitals and health centers, a large hospital in Portugal, and a medical clinic in Romania, with 53.6% and 6.71% response rates for the ICT and healthcare professionals, respectively. Its findings indicate the necessity of establishing individual cybersecurity departments to monitor assets and attitudes while underlying the importance of continuous security awareness training programs. The analysis of our results assists in comprehending the countermeasures, which have been implemented in the healthcare institutions, and consequently enhancing cybersecurity defense, while reducing the risk surface.
The general idea of the AMBER/Child Alert System is that by broadcasting and distributing information about a missing child to the community, the public's involvement can trigger critical feedback that would have otherwise been ignored. This feedback, in several cases, can be proved decisive in finding the missing child. Despite the efforts at country and European level to effectively address the issue of missing children, a number of key challenges remain open, including lack of location-focused distribution of alerts, insufficient capture and diffusion of information, and lack of a mechanism that uses and merges all available sources of information. The aim of this paper is to present a novel approach for handling such challenges through a data analytics platform and a mobile application available to all citizens. Using the active research fields of human mobility pattern analysis and machine learning, we show that missing children investigations, as well as search and rescue operations, can be actively supported and enhanced when multiple data sources are combined and analyzed.
The increase of cyber-attacks raised security concerns for critical assets worldwide in the last decade. Leading to more efforts spent towards increasing the cyber security among companies and countries. For the sake of enhancing cyber security, representation and testing of attacks have prime importance in understanding system vulnerabilities. One of the available tools for simulating attacks on systems is the Meta Attack Language (MAL), which allows representing the effects of certain cyber-attacks. However, only understanding the component vulnerabilities is not enough in securing enterprise systems. Another important factor is the 'human', which constitutes the biggest 'insider threat'. For this, Security Behavior Analysis (SBA) helps understanding which system components that might be directly affected by the 'human'. As such, in this work, the authors present an approach for integrating user actions, so called "security behavior", by mapping SBA to a MAL-based language through MITRE ATT&CK techniques.CCS Concepts: • Security and privacy → Domain-specific security and privacy architectures.
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