Biblio

The Enterprise Architecture and Systems Engineering communities are often faced with complexity barriers that develop due to the fact that modern systems must be agile and resilient. This requires dynamic changes to the system so as to adapt to changing missions as well as changes in the internal and external environments. The requirement is not entirely new, but practitioners need guidance on how to manage the life cycle of such systems. This is a problem because we must be able to architect systems by alleviating the difficulties in systems life cycle management (e.g., by helping the enterprise- or systems engineer organise and maintain models and architecture descriptions of the system of interest). Building on Pask’s conversation theoretic model of aware (human or machine) individuals, the paper proposes a reference model for systems that maintain their own models real time, act efficiently, and create system-level awareness on all levers of aggregation.

Model Based Systems Engineering (MBSE) adds efficiency during all phases of the design lifecycle. MBSE tools enforce design policies and rules to capture the design elements, inter-element relationships, and their attributes in a consistent manner. The system elements, and attributes are captured and stored in a centralized MBSE database for future retrieval. Systems that depend on computer networks can be designed using MBSE to meet cybersecurity and resilience requirements. At each step of a structured systems engineering methodology, decisions need to be made regarding the selection of architecture and designs that mitigate cyber risk and enhance cyber resilience. Detailed risk and decision analysis methods involve complex models and computations which are often characterized as a Big Data analytic problem. In this paper, we argue in favor of using graph analytic methods with model based systems engineering to support risk and decision analyses when engineering cyber resilient systems.