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Updated: Dec 20, 2025

An R-Based Landscape Validation of a Competing Risk Model
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RESPOnSE-A Framework for Enforcing Risk-Aware Security Policies in Constrained Dynamic Environments.

Christina Michailidou1,2, Vasileios Gkioulos3, Andrii Shalaginov3

  • 1Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, 56124 Pisa, Italy.

Sensors (Basel, Switzerland)
|May 28, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces RESPOnSE, a framework for efficient access control in constrained networks. It combines Attribute-Based Access Control and Role-Based Access Control for risk-aware policy enforcement by edge devices.

Keywords:
constrained dynamic systemsmulticriteria decision makingpolicy based managementsecuritytopsis

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Area of Science:

  • Computer Science
  • Network Security
  • Cybersecurity

Background:

  • Constrained dynamic networks face challenges in enforcing fine-grained access control due to device limitations.
  • Edge devices require efficient mechanisms for monitoring, controlling actions, and regulating resource access.

Purpose of the Study:

  • To present RESPOnSE, a framework for specifying and enforcing security policies in constrained dynamic networks.
  • To address computational limitations by offloading tasks to high-tier nodes.

Main Methods:

  • RESPOnSE integrates Attribute-Based Access Control (ABAC) and Role-Based Access Control (RBAC).
  • It employs a compensatory multicriteria decision-making algorithm using Euclidean distance for policy enforcement.
  • Low-tier nodes perform risk-aware policy enforcement based on runtime attribute values.

Main Results:

  • The framework enables efficient and effective access control in resource-constrained environments.
  • Computational burden is managed by transferring processing to high-tier nodes.
  • Risk-aware enforcement is achieved at the edge through a decision-making algorithm.

Conclusions:

  • RESPOnSE provides a robust solution for access control in challenging network conditions.
  • The hybrid ABAC/RBAC model and decision-making algorithm enhance security and efficiency.
  • The framework is suitable for dynamic networks with limited edge device capabilities.