Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Lack of Security of Networked Medical Equipment in Radiology
13
Zitationen
2
Autoren
2015
Jahr
Abstract
OBJECTIVE. There are few articles in the literature describing the security and safety aspects of networked medical equipment in radiology departments. Most radiologists are unaware of the security issues. We review the security of the networked medical equipment of a typical radiology department. MATERIALS AND METHODS. All networked medical equipment in a radiology department was scanned for vulnerabilities with a port scanner and a network vulnerability scanner, and the vulnerabilities were classified using the Common Vulnerability Scoring System. A network sniffer was used to capture and analyze traffic on the radiology network for exposure of confidential patient data. We reviewed the use of antivirus software and firewalls on the networked medical equipment. USB ports and CD and DVD drives in the networked medical equipment were tested to see whether they allowed unauthorized access. Implementation of the virtual private network (VPN) that vendors use to access the radiology network was reviewed. RESULTS. Most of the networked medical equipment in our radiology department used vulnerable software with open ports and services. Of the 144 items scanned, 64 (44%) had at least one critical vulnerability, and 119 (83%) had at least one high-risk vulnerability. Most equipment did not encrypt traffic and allowed capture of confidential patient data. Of the 144 items scanned, two (1%) used antivirus software and three (2%) had a firewall enabled. The USB ports were not secure on 49 of the 58 (84%) items with USB ports, and the CD or DVD drive was not secure on 17 of the 31 (55%) items with a CD or DVD drive. One of three vendors had an insecure implementation of VPN access. CONCLUSION. Radiologists and the medical industry need to urgently review and rectify the security issues in existing networked medical equipment. We hope that the results of our study and this article also raise awareness among radiologists about the security issues of networked medical equipment.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.260 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.116 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.493 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.438 Zit.