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Behavior is a product of both the situation (e.g., cultural influences, social roles, and the presence of bystanders) and of the person (e.g., personality characteristics). Subfields of psychology tend to focus on one influence or behavior over others. Situationism is the view that our behavior and actions are determined by our immediate environment and surroundings. In contrast, dispositionism holds that our behavior is determined by internal factors (Heider, 1958).
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Some individuals interpret life events as a consequence of their personal choices and actions, while others believe that outcomes are dictated by fate or destiny. This divergence in perspective has been examined in psychological and cross-cultural studies, particularly in relation to religious faith and cultural beliefs about causality.Fate and Personal ResponsibilityPeople who emphasize personal responsibility view events as direct consequences of their decisions. For instance, breaking a leg...
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Poster: Using Gini Impurity to Mine Attribute-based Access Control Policies with Environment Attributes.

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Summary
This summary is machine-generated.

This study introduces a new Attribute-Based Access Control (ABAC) policy mining algorithm. It effectively uses environment attributes and gini impurity to create fewer, more precise access rules.

Keywords:
ABACEnvironment attributesGini impurityPolicy mining

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Area of Science:

  • Computer Science
  • Information Security

Background:

  • Attribute-Based Access Control (ABAC) systems enhance security by using attributes for access decisions.
  • Incorporating environment attributes into ABAC allows for more dynamic and fine-grained access control.
  • Existing ABAC methods may not fully leverage environmental context for rule generation.

Purpose of the Study:

  • To develop an ABAC policy mining algorithm that integrates environment attributes.
  • To enhance access control granularity and dynamism.
  • To minimize the number of generated access control rules.

Main Methods:

  • A novel ABAC policy mining algorithm is proposed.
  • The algorithm considers subject, object, and environment attributes.
  • Gini impurity is utilized for efficient rule formation and policy minimization.

Main Results:

  • The algorithm effectively mines ABAC policies incorporating environmental factors.
  • The use of gini impurity leads to a minimized set of access control rules.
  • Experimental evaluation demonstrates the practical effectiveness of the proposed approach.

Conclusions:

  • The developed algorithm offers a practical solution for fine-grained access control in ABAC systems.
  • Integrating environment attributes significantly enhances the dynamic nature of access decisions.
  • The method provides an efficient way to generate concise and effective ABAC policies.