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Type: Conference paper
Title: Discovering "unknown known" security requirements
Author: Rashid, A.
Naqvi, S.
Ramdhany, R.
Edwards, M.
Chitchyan, R.
Ali Babar, M.
Citation: Proceedings of the 38th International Conference on Software Engineering, 2016 / vol.14-22-May-2016, pp.866-876
Publisher: ACM
Issue Date: 2016
Series/Report no.: International Conference on Software Engineering
ISBN: 9781450339001
ISSN: 0270-5257
Conference Name: 38th International Conference on Software Engineering (ICSE '16) (14 May 2016 - 22 May 2016 : Austin, TX)
Statement of
Awais Rashid, Syed Asad Ali Naqvi, Rajiv Ramdhany, Matthew Edwards, Ruzanna Chitchyan, M. Ali Babar
Abstract: Security is one of the biggest challenges facing organisations in the modern hyper-connected world. A number of theoretical security models are available that provide best practice security guidelines and are widely utilised as a basis to identify and operationalise security requirements. Such models often capture high-level security concepts (e.g., whitelisting, secure configurations, wireless access control, data recovery, etc.), strategies for operationalising such concepts through specific security controls, and relationships between the various concepts and controls. The threat landscape, however, evolves leading to new tacit knowledge that is embedded in or across a variety of security incidents. These unknown knowns alter, or at least demand reconsideration of the theoretical security models underpinning security requirements. In this paper, we present an approach to discover such unknown knowns through multi-incident analysis. The approach is based on a novel combination of grounded theory and incident fault trees. We demonstrate the effectiveness of the approach through its application to identify revisions to a theoretical security model widely used in industry.
Keywords: Security requirements, incident analysis, grounded theory
Rights: © 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.
RMID: 0030056664
DOI: 10.1145/2884781.2884785
Appears in Collections:Computer Science publications

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