{"title":"Building a Scientific Foundation for Security: Multilayer Network Model Insights for System Security Engineering","authors":"Adam D. Williams, Susan A. Caskey","doi":"10.1002/iis2.13143","DOIUrl":null,"url":null,"abstract":"<p>To help incorporate security into INCOSE's Systems Engineering Vision 2035, the INCOSE systems security engineering working group endorses a paradigmatic shift to reframe systems security as trustworthy, loss-driven, and capabilities-based. Similar research out of Sandia National Laboratories has explored cutting-edge approaches to systems security for national security applications. Together, these efforts highlight the need for—-and a path toward—-a scientific foundation for security. Leveraging underlying tenets of systems theory, observed security heuristics, and the concepts emerging from INCOSE's SSE working helps triangulate a set of “first principles” as part of a scientific foundation for security as an emergent systems property that incorporates traditional physical security designs, cyber security architectures, and personnel security programs—-as well as the (often ignored) interactions between them. These first principles, in turn, are the basis for a set of derived systems security performance axioms that support current INCOSE SSE working efforts. We have demonstrated this approach's logic and designability with a multilayer network model-based approach for systems security. The structure of this scientific foundation for security offers additional, innovative opportunities to achieve desired levels of trustworthiness, creative mechanisms to meet needs, innovative loss-driven approaches, and enhanced capabilities—-all aimed at producing more efficient and effective systems security solutions against current and emerging threats, uncertainties, and complexities.</p>","PeriodicalId":100663,"journal":{"name":"INCOSE International Symposium","volume":"34 1","pages":"224-238"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INCOSE International Symposium","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/iis2.13143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To help incorporate security into INCOSE's Systems Engineering Vision 2035, the INCOSE systems security engineering working group endorses a paradigmatic shift to reframe systems security as trustworthy, loss-driven, and capabilities-based. Similar research out of Sandia National Laboratories has explored cutting-edge approaches to systems security for national security applications. Together, these efforts highlight the need for—-and a path toward—-a scientific foundation for security. Leveraging underlying tenets of systems theory, observed security heuristics, and the concepts emerging from INCOSE's SSE working helps triangulate a set of “first principles” as part of a scientific foundation for security as an emergent systems property that incorporates traditional physical security designs, cyber security architectures, and personnel security programs—-as well as the (often ignored) interactions between them. These first principles, in turn, are the basis for a set of derived systems security performance axioms that support current INCOSE SSE working efforts. We have demonstrated this approach's logic and designability with a multilayer network model-based approach for systems security. The structure of this scientific foundation for security offers additional, innovative opportunities to achieve desired levels of trustworthiness, creative mechanisms to meet needs, innovative loss-driven approaches, and enhanced capabilities—-all aimed at producing more efficient and effective systems security solutions against current and emerging threats, uncertainties, and complexities.