Community-based Self Generation of Policies and Processes for Assets: Concepts and Research Directions

Abstract With the advancement in the technology, deploying connected assets—especially intelligent autonomous assets—to obtain the evolving picture of dynamic environments are fast becoming a reality—and a need—for effective and efficient decision making. In such environments, these assets need to function in unison with each other to achieve the goals, and especially in a collaborative environments (e.g., coalition environments) they need to respect the constraints placed on them by the collective as well as by the owner parties. Typically, policies are used to govern such constraints and interactions, but the existing state-of-the-art relies on predefined user policies to achieve the effect, which is not scalable nor practical in collaborative and dynamic environments. Motivated by this observation and the recent uptake in learning technologies, in this paper, we present our vision on a framework that can (a) employ multiple techniques to create domain knowledge that can help assets to determine which policies are critical for which context, how to solve conflicts among policies, and how to autonomously generate and refine existing policies; (b) represent knowledge in a localized wiki-like approach so that fault tolerant knowledge discovery is supported; (c) provide efficient query interface for assets to discover needed knowledge in a secure manner; and (d) contextualize knowledge so as to enable other similar assets to quickly bootstrap or initialize themselves in unknown contexts when new events occur.
  • Elisa Bertino (Purdue)
  • Geeth de Mel (IBM UK)
  • Alessandra Russo (Imperial)
  • Seraphin Calo (IBM US)
  • Dinesh Verma (IBM US)
Date Dec-2017
Venue 1st IEEE Big Data International Workshop on Policy-based Autonomic Data Governance (PADG)