Cybersecurity Policies and Their Impact on Dynamic Data Driven Application Systems

Abstract

The objective of this paper is to explore how cybersecurity policies pertaining to data privacy, data acquisition, data fusion and data mining, impact the feasibility and functionality of Dynamic Data Driven Application Systems (DDDAS). In this work, a social media network model, will serve as the DDDAS of study in order to reveal how varying cybersecurity policies, could alter the functionality and usefulness of the system. At its fundamental level, the social media network model proposed in this work, TEchnology PHobia readiness CONdition (TEPHCON), seeks to serve as a decision support system that dynamically captures and visualizes society's affinity/aversion towards current or emerging technologies. However, at its core, this DDDAS is built upon a data platform that is highly susceptible to changes in cybersecurity policies. For example, a change in cybersecurity policies pertaining to freedom of speech in a cyber environment, may significantly alter the access and availability of publicly-available data. On the other hand, a more hands-off cyber policy pertaining to who controls cyber infrastructure networking speeds, may result in an imbalance of data that may threaten the veracity of TEPHCON. Therefore, cybersecurity policies are an integral component of DDDAS systems such as TEPHCON and as such, their impact should be explored in detail.