1. When Milliseconds Matter: Evaluating the Vulnerability of High Frequency Trading Models to Adversarial Manipulation Restricted (Penn State Only) Author: Chakraborty, Karmabir Title: When Milliseconds Matter: Evaluating the Vulnerability of High Frequency Trading Models to Adversarial Manipulation Graduate Program: Data Analytics Keywords: High-Frequency Trading (HFT)Deep LearningAdversarial AttacksAlgorithmic TradingLimit Order Book (LOB)FI-2010 DatasetConvolutional Neural Networks (CNNs)Long Short-Term Memory (LSTM)Fast Gradient Sign Method (FGSM)Projected Gradient Descent (PGD).High Frequency TradingLimit Order BooksFI-2010Convolutional Neural NetworksLong Short-Term MemoryFast Gradient Sign MethodProjected Gradient DescentFinanceDeepLOB File: Login to Download Committee Members: Hajime Shimao, Thesis Advisor/Co-AdvisorChengfei Wang, Committee MemberRaghu Sangwan, Program Head/ChairWarut Khern-am-nuai, Committee Member