Relevance Based Secure and Scalable Decentralized Data Sharing System
Data has proliferated to astronomical proportions; thus, big data has become the driving force behind many machine learning innovations. However, the incessant generation of data in the information age poses a needle in the haystack problem. It has become challenging to determine useful data from a...
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| Format: | Dissertation |
| Language: | English |
| Published: |
ProQuest Dissertations & Theses
01-01-2020
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| Online Access: | Get full text |
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| Summary: | Data has proliferated to astronomical proportions; thus, big data has become the driving force behind many machine learning innovations. However, the incessant generation of data in the information age poses a needle in the haystack problem. It has become challenging to determine useful data from a heap of irrelevant ones. This problem has resulted in a quality over quantity issue in data science where enormous data gets generated, but most of it is irrelevant. Furthermore, most of the data and the resources needed to train machine learning models effectively are owned by major tech companies, resulting in a centralization problem. GAFA (Google, Apple, Facebook, Amazon) tend to monopolize data, resulting in these organizations bringing in the most revenue. As a result, big data has been termed the new oil because of the valuable asset it has transformed into in recent years. Consequently, big data security has become an area of immense importance. Data breaches, the creation of data silos, the vastness of data, and personal privacy concerns are all issues associated with big data security.In this dissertation, the goal is to address the problems highlighted above. A relevance-based approach to decentralized data-sharing that provides better security and accessibility to relevant data than the traditional centralized and decentralized way of data sharing is presented. A new consensus mechanism known as the Proof of Common Interest (PoCI) that determines relevant data from irrelevant ones is proposed as well. To this end, the practicality and effectiveness of the PoCI powered decentralized network (in terms of security and the advantage of having relevant data) is demonstrated by presenting problems that this approach has been instrumental in solving. These problems include the role the PoCI network plays in the provision of edge intelligence [26] as well as the mitigation of data poisoning attacks. The PoCI network is also used to develop a novel encryption mechanism that aims to decrypt messages in the future based on the occurrence of an event [28]. Finally, the PoCI has been used in conjunction with Named Data Networking to solve the connectivity issues in highly dynamic networks [29]. Numerical results obtained from simulations are presented to support the above-mentioned claims. |
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| ISBN: | 9798728226789 |