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Securing cloud storage brokerage systems through threat models

  • Cloud storage brokerage is an abstraction aimed at providing value-added services. However, Cloud Service Brokers are challenged by several security issues including enlarged attack surfaces due to integration of disparate components and API interoperability issues. Therefore, appropriate security risk assessment methods are required to identify and evaluate these security issues, and examine the efficiency of countermeasures. A possible approach for satisfying these requirements is employment of threat modeling concepts, which have been successfully applied in traditional paradigms. In this work, we employ threat models including attack trees, attack graphs and Data Flow Diagrams against a Cloud Service Broker (CloudRAID) and analyze these security threats and risks. Furthermore, we propose an innovative technique for combining Common Vulnerability Scoring System (CVSS) and Common Configuration Scoring System (CCSS) base scores in probabilistic attack graphs to cater for configuration-based vulnerabilities which are typicallyCloud storage brokerage is an abstraction aimed at providing value-added services. However, Cloud Service Brokers are challenged by several security issues including enlarged attack surfaces due to integration of disparate components and API interoperability issues. Therefore, appropriate security risk assessment methods are required to identify and evaluate these security issues, and examine the efficiency of countermeasures. A possible approach for satisfying these requirements is employment of threat modeling concepts, which have been successfully applied in traditional paradigms. In this work, we employ threat models including attack trees, attack graphs and Data Flow Diagrams against a Cloud Service Broker (CloudRAID) and analyze these security threats and risks. Furthermore, we propose an innovative technique for combining Common Vulnerability Scoring System (CVSS) and Common Configuration Scoring System (CCSS) base scores in probabilistic attack graphs to cater for configuration-based vulnerabilities which are typically leveraged for attacking cloud storage systems. This approach is necessary since existing schemes do not provide sufficient security metrics, which are imperatives for comprehensive risk assessments. We demonstrate the efficiency of our proposal by devising CCSS base scores for two common attacks against cloud storage: Cloud Storage Enumeration Attack and Cloud Storage Exploitation Attack. These metrics are then used in Attack Graph Metric-based risk assessment. Our experimental evaluation shows that our approach caters for the aforementioned gaps and provides efficient security hardening options. Therefore, our proposals can be employed to improve cloud security.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Kennedy A. TorkuraORCiD, Muhammad Ihsan Haikal SukmanaORCiDGND, Michael Meinig, Anne V. D. M. KayemGND, Feng ChengGND, Christoph MeinelORCiDGND, Hendrik Graupner
DOI:https://doi.org/10.1109/AINA.2018.00114
ISBN:978-1-5386-2195-0
ISSN:1550-445X
Titel des übergeordneten Werks (Englisch):Proceedings IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)
Verlag:IEEE
Verlagsort:New York
Publikationstyp:Sonstiges
Sprache:Englisch
Datum der Erstveröffentlichung:13.08.2018
Erscheinungsjahr:2018
Datum der Freischaltung:07.03.2022
Freies Schlagwort / Tag:Cloud-Security; Secure Configuration; Security Metrics; Security Risk Assessment; Threat Models
Seitenanzahl:10
Erste Seite:759
Letzte Seite:768
Organisationseinheiten:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Peer Review:Referiert
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