服務喔!請把握機會。 工作經歷 教授 • 國立政治大學 六月Present | Taipei, Taiwan Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. 學歷 國立台灣政治大學 經濟學 •Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. 技能 Word Java Canva Excel Visio MySQL C# 語言 English — 母語或雙語
入集團UUID單一識別碼分享架構。 學歷 德明財經科技大學 資訊科技系 •私立學校難度較低都拿第一。 帶領同學參加競賽成績都不錯。 技能 C# C# .Net MVC c#.net c# windows form VB.NET vb.net SAP SQL Server Oracle SyBase DB2 SQL(IBM) Web Development Vue.js .NET Core 語言 English — 中階 Japanese — 中階
the campus to continue to enrich myself. Elective Courses-8 subjects with a total average score :85.4 and GPA : 3.9. ➤ Advanced artificial intelligence: use Google Colab to analyze pm2.5 air pollution data, and use linear regression to predict stocks, use C# to write fish identification in the final report and automatically bring it into the optional cooking menu. ➤ Advanced data mining and huge data analysis: Use python and use google API search engine to compose automatic answering robots. ➤ Image processing: Use Visual studio 2012 C#
I am a Graduate Student at Penn State, where I attend the laboratory led by Liu Peng, the director of the Cyber Security Lab.My research focuses on Network and System Security, and Deep Learning.
Research Experience
Research Assistant
Pennsylvania State University• 08.2023 - Present
Reinforcement Learning for Advanced Persistent Threat
Analyzing real-world enterprise login data and network data to reconstruct the actual network environment.
Simulating the attack behavior of APT groups such as APT28 or APT41.
Academia Sinica• 09.2021 - 06.2023
Graph-based Neural Attack Behavior Detection and Alignment with Kernel Audit Logs for Advanced Persistent Threats
Simulated APT attack on Linux and Windows
Developed a theory for efficiently reducing kernel audit logs to ensure the high quality of behavior detection
Developed models leveraging graph embedding to correlate and mine suspicious behavior in audit logs
Modeling Threat Representation through Building Cyber Threat Knowledge Base for Advanced Persistent Threats
Developed models to extract semantic context from cyber threat intelligence platforms for generating provenance graphs
Using Honeypot Logs and Packets for Identifying Network Attack Patterns and their Signature
Utilizing BERT-based models to analyze packets and logs from honeypots provided by Soft Bank
P.-Y. Tseng, P.-C. Lin, Edy Kristianto, Vehicle Theft Detection by Generative Adversarial Networks on Driving Behavior. Engineering Applications of Artificial Intelligence (published) [Paper]
Project
Reinforcement Learning for Advanced Persistent Threat
A novel approach to defend against APT attacks, specifically targeting lateral movement.
To formulate APT attack into Observable Markov Decision Process (POMDP) problems
APT Discovery using OSINT and Network & System Logs
Integrated Open-source intelligence, Cyber threat intelligence, and MITRE ATT&CK framework into a cyber threat knowledge base, and developed neural network architectures to analyze and detect APT attacks in a multi-host environment.
Aligned the observed evidence to adversary lifecycle and correlated the relation between the detected
I am a Graduate Student at Penn State, where I attend the laboratory led by Liu Peng, the director of the Cyber Security Lab.My research focuses on Network and System Security, and Deep Learning.
Research Experience
Research Assistant
Pennsylvania State University• 08.2023 - Present
Reinforcement Learning for Advanced Persistent Threat
Analyzing real-world enterprise login data and network data to reconstruct the actual network environment.
Simulating the attack behavior of APT groups such as APT28 or APT41.
Academia Sinica• 09.2021 - 06.2023
Graph-based Neural Attack Behavior Detection and Alignment with Kernel Audit Logs for Advanced Persistent Threats
Simulated APT attack on Linux and Windows
Developed a theory for efficiently reducing kernel audit logs to ensure the high quality of behavior detection
Developed models leveraging graph embedding to correlate and mine suspicious behavior in audit logs
Modeling Threat Representation through Building Cyber Threat Knowledge Base for Advanced Persistent Threats
Developed models to extract semantic context from cyber threat intelligence platforms for generating provenance graphs
Using Honeypot Logs and Packets for Identifying Network Attack Patterns and their Signature
Utilizing BERT-based models to analyze packets and logs from honeypots provided by Soft Bank
P.-Y. Tseng, P.-C. Lin, Edy Kristianto, Vehicle Theft Detection by Generative Adversarial Networks on Driving Behavior. Engineering Applications of Artificial Intelligence (published) [Paper]
Project
Reinforcement Learning for Advanced Persistent Threat
A novel approach to defend against APT attacks, specifically targeting lateral movement.
To formulate APT attack into Observable Markov Decision Process (POMDP) problems
APT Discovery using OSINT and Network & System Logs
Integrated Open-source intelligence, Cyber threat intelligence, and MITRE ATT&CK framework into a cyber threat knowledge base, and developed neural network architectures to analyze and detect APT attacks in a multi-host environment.
Aligned the observed evidence to adversary lifecycle and correlated the relation between the detected