Abstract
Data tampering is one of the most intriguing personal information security concerning issues in online business portals. For various individual or business purposes, clients need to share their personal information with these online business portals. Upon taking conveniences from this sharing of information about an individual, online business sites accumulate client data including client’s most sensitive information for running different data analysis without taking the clients’ authorization. In a view to proposing suggestions, data analysis may need to be done in the online business portals. A recommender system or framework creates an automated personalization on a rundown of items based on the users’ preference of searching any product over the portal. These days, the recommender system or framework is the part and parcel to the online marketing and business portals. However, secure control of client information is missing to some extent in such systems. Blockchain technology guarantees security in data manipulation for the clients in these online portals since it is a secure distributed ledger for storing data transaction. This paper presents a privacy-preserving or privacy-securing platform for recommender framework or system utilizing blockchain technology. The distributed ledger attribute of blockchain gives any client a verified domain where information is utilized for analysis with his/her required consents. Under this platform, clients get rewards (i.e., points, discounts) from the proposed online based company for sharing their information to figure out and propose relevant suggestions.
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- 1.
We assume that \(ID_g\) is a trusted party of our platform.
- 2.
We assume that TDS is a trusted party of our platform.
- 3.
Users’ permission were taken when they confirm to join our platform.
- 4.
Platform will ask about the permission separately.
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This work is partially supported by Institute of Energy, Environment, Research and Development (IEERD), University of Asia Pacific (UAP), Bangladesh.
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Omar, A.A., Bosri, R., Rahman, M.S., Begum, N., Bhuiyan, M.Z.A. (2019). Towards Privacy-preserving Recommender System with Blockchains. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_9
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