Prevention of Personally Identifiable Information Leakage in E-commerce via Offline Data Minimisation and Pseudonymisation


Authors : Mukuka Kangwa; Charles S. Lubobya; Jackson Phiri

Volume/Issue : Volume 6 - 2021, Issue 1 - January

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/3quNqcW

This paper proposes the use of Offline Data minimization and Pseudonymisation to protect users’ Personally Identifiable Information (PII) and privacy via the use of physical and logical partitions implemented with hardware and software algorithms. Data is most vulnerable to leakage if made accessible via the Internet. Several approaches are being used to protect online data. However, the numerous instances where online data has been leaked shows the need to enhance the existing solutions. Further, the privacy of individuals using the internet has been compromised on several occasions. The compromise in some instances has resulted in victims being defrauded. The research aims to protect the ecommerce user’s privacy while online by using random pseudo IDs. The research plans to formulate an algorithm to generate random IDs that can be used to transact online while preventing online profiling that is possible via the use of static Pseudo IDs. The Random ID generator algorithm will have the ability to uniquely trace back to the user of a given Random pseudo ID

Keywords : Pseudonymisation, Anonymization, Offline Data, Leakage Prevention, Physical And Logical Separation, PII Protection.

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Paper Submission Last Date
31 - October - 2021

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