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AI-driven Approach for Access Control List Management

Authors:
Nader Shahata
Hirokazu Hasegawa
Hiroki Takakura

Keywords: Access Control; Cyber Security; Network; Artificial Intelligence.

Abstract:
With the increasing dependence on digital systems and the pervasive nature of cyber threats, ensuring secure access to information and resources has grown to be a crucial component of our activities online. Access control lists serve as foundational frameworks that govern the authorization and authentication processes within computer systems. This paper examines how do access control lists can be employed effectively in the field of cybersecurity and digs into its important role in protecting sensitive data, mitigating risks, and safeguarding against unauthorized access. Access control lists play a vital role in ensuring the security and confidentiality of sensitive information and resources. Traditionally, access control has relied on predefined rules and policies to determine who has the eligibility in accessing which data. However, the rise of Artificial Intelligence (AI) has introduced new possibilities and challenges in the field of access control. This paper explores the impact of AI on access control lists, examining the benefits and potential concerns associated with the integration of AI technologies. In order to secure the organization’s network, we propose an AI-driven ACL management system which generates ACL automatically. By managing the network traffic with the generated ACL, the system supports network analysts to prioritize certain threats that require immediate response. By discussing the effectiveness of the system, we explore the possibility of AI-driven ACL management.

Pages: 52 to 58

Copyright: Copyright (c) IARIA, 2023

Publication date: September 25, 2023

Published in: conference

ISSN: 2162-2116

ISBN: 978-1-68558-092-6

Location: Porto, Portugal

Dates: from September 25, 2023 to September 29, 2023