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BISCUIT - Blockchain Security Incident Reporting Based on Human Observations
Putz, Benedikt
, Vielberth, Manfred
und Pernul, Günther
(2022)
BISCUIT - Blockchain Security Incident Reporting Based on Human Observations.
In: ARES 2022: The 17th International Conference on Availability, Reliability and Security, 23-26 August 2022, Vienna.
Veröffentlichungsdatum dieses Volltextes: 19 Sep 2022 12:43
Konferenz- oder Workshop-Beitrag
DOI zum Zitieren dieses Dokuments: 10.5283/epub.52888
Dies ist die aktuelle Version dieses Eintrags.
Zusammenfassung
Security incidents in blockchain-based systems are frequent nowadays, which calls for more structured efforts in incident reporting and response. To improve the current status quo of reporting incidents on blogs and social media, we propose a decentralized incident reporting and discussion system. Our approach guides users (security novices) towards a classification of their observations using a ...
Security incidents in blockchain-based systems are frequent nowadays, which calls for more structured efforts in incident reporting and response. To improve the current status quo of reporting incidents on blogs and social media, we propose a decentralized incident reporting and discussion system. Our approach guides users (security novices) towards a classification of their observations using a tiered taxonomy of blockchain incidents. Questions based on previous incidents interactively support the classification. Post submission a security incident response committee then discusses these observations on our decentralized platform to decide on an appropriate response. For evaluation, we implement our model as a decentralized application and demonstrate its practical suitability in a preliminary user study.
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Details
| Dokumentenart | Konferenz- oder Workshop-Beitrag (Paper) | ||||
| ISBN | 978-1-4503-9670-7 | ||||
| Buchtitel: | ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security | ||||
|---|---|---|---|---|---|
| Verlag: | Association for Computing Machinery | ||||
| Ort der Veröffentlichung: | New York, NY, USA | ||||
| Sonstige Reihe: | ARES '22 | ||||
| Nummer des Zeitschriftenheftes oder des Kapitels: | 27 | ||||
| Seitenbereich: | S. 1-6 | ||||
| Datum | 23 August 2022 | ||||
| Zusätzliche Informationen (Öffentlich) | This is the submitted version, which is longer than the shortened version accepted at ARES 2022. | ||||
| Institutionen | Wirtschaftswissenschaften > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik I - Informationssysteme (Prof. Dr. Günther Pernul) Informatik und Data Science > Fachbereich Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik I - Informationssysteme (Prof. Dr. Günther Pernul) | ||||
| Identifikationsnummer |
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| Stichwörter / Keywords | Distributed Ledger, Incident Detection, Blockchain, Human-as-a-Security-Sensor | ||||
| Dewey-Dezimal-Klassifikation | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik 300 Sozialwissenschaften > 330 Wirtschaft | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Nein, diese Version wurde noch nicht begutachtet (bei preprints) | ||||
| An der Universität Regensburg entstanden | Ja | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-528889 | ||||
| Dokumenten-ID | 52888 |
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