Data integrity verification for cloud storage

• Main Author: Zhang, Haoran
• Other Authors: Soong Boon Hee
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science; Data integrity verification
• Online Access: https://hdl.handle.net/10356/176912
• Institution: Nanyang Technological University

As Singapore cements its position as one of the world's largest bunkering hubs, the nation's economy increasingly relies on an efficient and transparent marine fuel supply chain.[1] This project aims to develop an advanced digital system for the collection, verification, and storage of bunkering data, ensuring data integrity and security. The system comprises two core parts: software and artificial intelligence (AI). The software part is focused on building a comprehensive system consisting of many software entities those include data collection, verification, encryption, and ensuring data integrity. Following that, the system aims to integrate with the AI data detection and AI data repair technologies we have developed. Moreover, the project deeply investigates key technical issues within the field of software engineering, such as concurrent and parallel programming, as well as automation programming, to improve system efficiency and reliability. The software system strives to accurately replicate real-world conditions as much as possible, including aspects such as data volume and data velocity. The AI part, through in-depth analysis of historical bunkering data, achieves a profound understanding of the relationships between different physical properties of marine fuels in pipelines. This advancement enables the prevention of illegal influences and modifications to the physical parameters within pipelines, effectively safeguarding against potential economic losses to the nation. Furthermore, for those non-fraudulent data affected by occasional errors in mass flow rate resulting in extreme values, our system will employ LSTM (Long Short-Term Memory) technology to accurately predict values, thereby minimizing losses due to legitimate errors caused by environmental factors. This project not only elevates the digitalization level of Singapore's marine fuel supply chain but also provides valuable practical experience and research outcomes for the application of software engineering and artificial intelligence.