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Scheduling algorithms for data-protection based on security-classification constraints to data-dissemination.

Mohammad Mahmood Otoom1, Mahdi Jemmali1,2,3, Wael M Khedr1,4

  • 1Department of Computer Science and Information, College of Science, Majmaah University, Majmaah, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces a novel private network model using two routers to manage data packet security levels, significantly reducing data leakages and enhancing information privacy through advanced scheduling algorithms.

Keywords:
AlgorithmsBig dataCybersecurityData-disseminationNetworksPacket-transmission

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Area of Science:

  • Computer Science
  • Network Security
  • Information Privacy

Background:

  • Rapid digital technology advancements introduce vulnerabilities in current inter-networking, leading to severe data leakages.
  • Data leakages pose significant threats to individual and public information privacy and security.

Purpose of the Study:

  • To design a private network model aimed at decreasing the incidence of data leakages.
  • To develop algorithmic techniques for scheduling network packets under security constraints.

Main Methods:

  • A two-router private network model was designed to manage transmitting network packet classification levels.
  • Eight algorithms were proposed to address the NP-hard packet scheduling problem with security classification constraints.
  • Techniques include dispatching rules and grouping methods to prevent simultaneous transmission of packets with the same security level.

Main Results:

  • The proposed 'best-classification groups' algorithm outperformed existing methods in 89.1% of generated instances, with an average gap of 0.001.
  • Testing on a real-world dataset showed the 'best-classification groups' algorithm was superior in 88.6% of cases, with an average gap under 0.001.

Conclusions:

  • The developed private network model and associated algorithms effectively minimize data leakages.
  • The proposed scheduling techniques offer a robust solution for enhancing network security and information privacy.