Visible to the public Research Challenges in Dynamic Policy-Based Autonomous Security

TitleResearch Challenges in Dynamic Policy-Based Autonomous Security
Publication TypeConference Paper
Year of Publication2017
AuthorsCalo, S., Lupu, E., Bertino, E., Arunkumar, S., Cirincione, G., Rivera, B., Cullen, A.
Conference Name2017 IEEE International Conference on Big Data (Big Data)
KeywordsAccess Control, authorisation, automatic security policy generation, autonomous systems, composability, consistent conflict free, dynamic policy, Estimation, generative policies, Government, learning (artificial intelligence), machine learning, Measurement, policy-based autonomous security management, privacy, pubcrawl, research and development, research challenges, research issues, resilience, Resiliency, security, security enforcement, security management, smart devices, Training
Abstract

Generative policies enable devices to generate their own policies that are validated, consistent and conflict free. This autonomy is required for security policy generation to deal with the large number of smart devices per person that will soon become reality. In this paper, we discuss the research issues that have to be addressed in order for devices involved in security enforcement to automatically generate their security policies - enabling policy-based autonomous security management. We discuss the challenges involved in the task of automatic security policy generation, and outline some approaches based om machine learning that may potentially provide a solution to the same.

URLhttp://ieeexplore.ieee.org/document/8258266/
DOI10.1109/BigData.2017.8258266
Citation Keycalo_research_2017