News analysis for the detection of cyber security issues in digital healthcare: A text mining approach to uncover actors, attack methods and technologies for cyber defense

Bertl, Markus News analysis for the detection of cyber security issues in digital healthcare: A text mining approach to uncover actors, attack methods and technologies for cyber defense. Young Information Scientist, 2019, vol. 4, pp. 1-15. [Journal article (Paginated)]

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English abstract

Objectives: This research reviews the possibilities of text mining in the area of cybercrime in digital healthcare showing how advanced information retrieval and natural language processing can be used to get insights. The aim is to mine news data to find out what is reported about digital healthcare, what security-related critical events happened, and what actors, attack methods, and technologies play a role there. Methods: Different projects already apply text mining successfully in the cyber domain. However, none of these are specifically tailored to threats in the digital healthcare sector or uses an as big data foundation for analysis. To achieve that goal, different text mining methodologies like fact extraction, semantic fields as well as statistical methods like frequency, correlation and trend calculations were used. The news data for the analysis was provided by the DocCenter from the National Defense Academy (DocCenter/NDA) of the Austrian Armed Forces. About 300,000 news articles were processed and analyzed. Additionally, the open source GDELT dataset was investigated. Results & Conclusion: The data points out that cyber threats are present in digital health technologies and cyberattacks are more and more threatening to organizations, governments, and every person them self. Not only hacker groups, firms, and governments are involved in these attacks, also terroristic organizations use cyberwarfare. That, together with the amount of technology in digital healthcare like pacemakers, IoT, wearables but also the importance of healthcare as critical infrastructure and the dependence on electronic health records makes our society vulnerable.

German abstract

Nachrichtenanalyse zur Erkennung von Cybersicherheitsproblemen im digitalen Gesundheitswesen: ein Text-Mining-Ansatz zur Aufdeckung von Akteuren, Angriffsmethoden und Technologien für die Cyber-Abwehr [Titel in deutscher Übersetzung]. Zielsetzung — Diese Publikation untersucht die Möglichkeiten, welche Text Mining im Bereich Cybercrime in Digital Healthcare bietet. Die Zielsetzung dieser Arbeit ist, herauszufinden was über Digital Healthcare berichtet wird, welche Akteure in dieser Domäne agieren und welche Angriffsmethoden und Technologien eine Rolle spielen. Forschungsmethoden — Verschiedene Projekte verwenden Text Mining erfolgreich im Cyber-Bereich, allerdings nicht spezifisch adaptiert auf die Anforderungen des Gesundheitswesens. Dazu wurden verschiedene Text-Mining-Methoden, wie Fact Extraction oder semantische Felder, sowie statistische Methoden wie Korrelationen oder Trendanalysen angewendet. Die Datengrundlage kam aus der Zentraldokumentation der Landesverteidigungsakademie (ZentDok/LVAk) des österreichischen Bundesheeres. Insgesamt wurden zirka 300.000 Artikel ausgewertet. Zusätzlich wurden die Metadaten des GDELT Datasets untersucht. Ergebnisse & Schlussfolgerung — Text Mining ist ein zentrales Werkzeug für Cybersecurity und Trendanalysen. Die Daten zeigen, dass Technologien im Bereich Digital Healthcare stetig zunehmen und Gefahren bergen. Diese werden auch gezielt von Organisationen, Staaten und Einzelpersonen ausgenutzt. Auch Terroristengruppen bedienen sich immer mehr Methoden der digitalen Kriegsführung, als Ergänzung zu klassischen Terrorangriffen. Das zeigt gemeinsam mit der Durchdringung des Gesundheitswesens von digitalen Technologien wie Herzschrittmacher, IoT, Wearables aber auch Krankenhausinformationssysteme und elektronische Patientenakten die Gefahr, die auf uns zukommt.

Item type: Journal article (Paginated)
Keywords: digital healthcare, cybercrime, text mining, media mining, new technologies, Watson Explorer, GDELT, OSInfo, OSINT, association rule mining, Digital Healthcare, Cybercrime, Text Mining, Media Mining, neue Technologien, Watson Explorer, GDELT, OSInfo, OSINT, Assoziationsanalyse
Subjects: L. Information technology and library technology > LH. Computer and network security.
Depositing user: Austrian E-LIS editors
Date deposited: 12 Nov 2019 07:25
Last modified: 23 Feb 2021 12:25
URI: http://hdl.handle.net/10760/39224

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