Analyzing Information Security Factors in Adoption of Intelligent Technologies for Medical Waste Management Systems

As the global production of medical waste continues to rise, effective management of medical waste has become essential. In the era of Industry 5.0, new intelligent technologies such as the Internet of Things (IoT) and blockchain have been applied in Medical waste management (MWM) systems. Despite t...

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Veröffentlicht in:IEEE transactions on consumer electronics 2024-02, Vol.70 (1), p.2066-2077
Hauptverfasser: Tang, Jing, Zheng, Qiao-Hong, Wang, Wei-Zhong, Deveci, Muhammet, Bacanin, Nebojsa, Zaidan, Aws Alaa
Format: Artikel
Sprache:eng
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Zusammenfassung:As the global production of medical waste continues to rise, effective management of medical waste has become essential. In the era of Industry 5.0, new intelligent technologies such as the Internet of Things (IoT) and blockchain have been applied in Medical waste management (MWM) systems. Despite their advantages, these technologies face challenges related to information security, influenced by various factors. Therefore, the information security factors identification and prioritization are essential for safety improvement. This paper aims to develop an FMEA-based framework to analyze the risks of information security factors of intelligent technologies applied to MWM systems. First, Probabilistic linguistic term sets (PLTSs) are employed to capture the uncertainty of assessment information. Then, the Criteria Importance through Intercriteria Correlation (CRITIC) method is utilized to handle the interactive relationship among risk criteria. Finally, the Preference Ranking Organization Method for Enrichment Evaluations-II (PROMETHEE-II) method prioritizes the risk of information security factors. An example of the MWM system in Istanbul, Turkey, is selected to illustrate the validity of the proposed framework. Third-party risk management is the most critical information security factor. The findings of this research can provide valuable insights and practical recommendations for decision-makers in MWM systems.
ISSN:0098-3063
1558-4127
DOI:10.1109/TCE.2023.3347650