Creating and analysing privacy policies of Malaysia e-commerce using personal data protection act

Despite legally binding agreements between users and website owners, users often overlook website privacy policies due to their length and complexity. Transparency in these policies is crucial, particularly in Malaysia, where regulatory agencies face challenges ensuring compliance with the personal data protection act (PDPA) of 2010 due to intricate language and complex legal clauses. Machine learning has been used to analyse privacy policies under various legal frameworks, but no dataset currently exists for the Malaysian PDPA. Thus, to bridge this gap, we introduce a pilot corpus of 50 privacy policies specifically tailored to the Malaysian PDPA. This dataset is analysed and made available for academic research, offering insights into privacy regulations and identifying trends in privacy policy transparency. Our findings pave the way for the development of tools to enhance compliance with PDPA standards and improve policy readability for users. The corpus also serves as a foundation for further research in privacy and data protection, encouraging the exploration of automated approaches for policy analysis and regulatory oversight.

Authors

Publication Details

Journal
Bulletin of Electrical Engineering and Informatics
Published
2025-05-02
DOI
https://doi.org/10.11591/eei.v14i3.8991
Citations
1
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
4.20
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article

Creating and analysing privacy policies of Malaysia e-commerce using personal data protection act

Mohd Noor Mohd Shariff, Manmeet Mahinderjit Singh, Zarul Fitri Zaaba, Nor Badrul Anuar et al.
1 citations
Bulletin of Electrical Engineering and Informatics
Privacy, Security, and Data Protection
4.20
article

Creating and analysing privacy policies of Malaysia e-commerce using personal data protection act

Mohd Noor Mohd Shariff, Manmeet Mahinderjit Singh, Zarul Fitri Zaaba, Nor Badrul Anuar, Auwal Shehu Ali
article en
1 citations

Abstract

Despite legally binding agreements between users and website owners, users often overlook website privacy policies due to their length and complexity. Transparency in these policies is crucial, particularly in Malaysia, where regulatory agencies face challenges ensuring compliance with the personal data protection act (PDPA) of 2010 due to intricate language and complex legal clauses. Machine learning has been used to analyse privacy policies under various legal frameworks, but no dataset currently exists for the Malaysian PDPA. Thus, to bridge this gap, we introduce a pilot corpus of 50 privacy policies specifically tailored to the Malaysian PDPA. This dataset is analysed and made available for academic research, offering insights into privacy regulations and identifying trends in privacy policy transparency. Our findings pave the way for the development of tools to enhance compliance with PDPA standards and improve policy readability for users. The corpus also serves as a foundation for further research in privacy and data protection, encouraging the exploration of automated approaches for policy analysis and regulatory oversight.

Bulletin of Electrical Engineering and InformaticsVol. 14(3)
Openalex Percentile: Top 8%
Privacy, Security, and Data Protection
4.20
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Creating and analysing privacy policies of Malaysia e-commerce using personal data protection act — Mohd Noor Mohd Shariff, Manmeet Mahinderjit Singh, et al. · Bulletin of Electrical Engineering and Informatics (2025) | TGRS Research Map | TGRS