School of Engineering Department of Computer Science and Engineering 115 Machine Learning Driven Web Log Tracing System Supervisor: IEONG Sze Chung Ricci / CSE Student: LEI Yongyu / CPEG Course: UROP1100, Fall Network Intrusion Detection System (NIDS), as the system aiming to detect intrusion by monitoring network activities, has become one critical part of cybersecurity. Web logs generated from network traffic of a system are mostly used as the objective of monitoring in a NIDS. Along with the prevalence of artificial intelligence (AI), to improve the performance of NIDSs, machine learning (ML) and deep learning (DL) methods have been widely applied to NIDSs to improve the accuracy of intrusion detection in recent three decades. This report trained and tested different ML or DL model based NIDSs using UNSW-NB15 dataset and summarized their performances of classifying network traffic records which would provide essential references for further proceeding the project. Optimization Problems in Blockchain Ecosystems Supervisor: KAFSHDAR GOHARSHADY Amir / CSE Student: ZHU Zherui / COGBM Course: UROP1100, Fall Fall Semester of 2021 is my first semester with professor Amir to do the UROP project: Optimization Problems in Blockchain Ecosystems, my learning target in this semester is mainly to learn knowledge related to the project focus: "finding more efficient algorithms for various optimization problems that are currently being solved inefficiently or imprecisely in the day-to-day operation of blockchains." The areas I have covered include the basic understanding of Blockchain. Understand algorithm optimization, such as parameterized algorithm. Then I read the Paper: Optimal Mining: Maximizing Bitcoin Miners’ Revenues which is closely related to the project focus. Finally, I chose A topic: A Survey of Attacks on Ethereum Smart Contracts (SoK) for study. This report will show my learning progress and achievement.