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Yubao Wu is an Assistant Professor of Computer Science at Georgia State University. He is also the Associate Director of Operation of the Evidence-Based Cybersecurity (EBCS) Research Group. He holds a Ph.D. (2016) in Computing and Information Science from Case Western Reserve University, OH, USA.

His research interests include evidence-based cybersecurity, big data analytics, data mining, databases, and artificial intelligence. Cybercriminals are utilizing modern internet products including social media platforms, instant message applications, Tor anonymous communications, and cryptocurrencies to facilitate crimes. His research aims at collecting open-source intelligence from the cybercriminals’ public online behavioral data such as ads, chats, and financial transactions. Numerous challenging research questions related to big data, data mining, databases, and artificial intelligence, are emerging in analyzing the online behavioral data. The open-source intelligence will help sociologists and law enforcement agencies study the behaviors of cybercriminals and develop effective interventions.

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Grants

• NSF D-ISN: TRACK 2: Building a Community to Use Intelligence from Online Underground Markets, National Science Foundation (NSF), Award #2039949, 02/28/2021-02/27/2023, $249,966, with Co-PI Robert Harrison (GSU) and Co-PI David Maimon (GSU).
• NSF RAPID: Threats from Underground Markets during the COVID-19 Pandemic, National Science Foundation (NSF), Award #2030636, 05/01/2020-04/30/2021, $58,871, with Co-PI David Maimon (GSU) and Co-PI Robert Harrison (GSU).
• DHS Open Source Intelligence in Online Stolen Data Markets - Assessment of Network Disruption Strategies, Department of Homeland Security (DHS) Center of Excellence (COE), 02/01/2020-01/31/2022, $350,000, with PI Marie Lavinia Ouellet (GSU) and Co-PI David Maimon (GSU).
• NSF CyberTraining: Pilot: EBCS-TMPS: An Evidence Based Cybersecurity Training and Mentorship Program for Students, National Science Foundation (NSF), Award #2017624, 08/01/2020-07/31/2022, $298,189, with PI David Maimon (GSU), Co-PI Robert Harrison (GSU), and Co-PI Richard Baskerville (GSU).
• Industry Fake TSL Certificates and their Prevalence on the Darknet and in Law Enforcement Records, Contract with Venafi, Inc, 10/01/2018-09/30/2019, $102,000, with PI David Maimon (GSU) and Co-PI Michael McGuire (University of Surrey).

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Selected Publications All Publications»

Google Scholar   h-index : 10   Citations : 367   ORCID   Scopus

• IEEE/ACM TCBB Fengpan Zhao, Pavel Skums, Alex Zelikovsky, Eric L. Sevigny, Monica Haavisto Swahn, Sheryl M. Strasser, Yan Huang, Yubao Wu. Computational Approaches to Detect Illicit Drug Ads and Find Vendor Communities Within Social Media Platforms. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), March, 2020.
• WWW Yuan Li, Guoren Wang, Yuhai Zhao, Feida Zhu, Yubao Wu. Towards K-Vertex Connected Component Discovery from Large Networks. World Wide Web (WWW), 23 (2): 799-830, 2020.
• IEEE TCSS Wenyi Tang, Guangchun Luo, Yubao Wu, Ling Tian, Xu Zheng, Zhipeng Cai. A Second-Order Diffusion Model for Influence Maximization in Social Networks. IEEE Transactions on Computational Social Systems (TCSS), 6(4): 702-714, 2019.
• The VLDB Journal Yubao Wu, Xiang Zhang, Yuchen Bian, Zhipeng Cai, Xiang Lian, Fengpan Zhao, Xueting Liao, and Syed M. R. Hussain. Second-Order Random Walk Based Proximity Measures in Graph Analysis: Formulations and Algorithms, The International Journal on Very Large Data Bases (The VLDB Journal), 27(1): 127-152 (2018).
• DASFAA Yuan Li, Yuhai Zhao, Guoren Wang, Feida Zhu, Yubao Wu, Shengle Shi. Effective k-Vertex Connected Component Detection in Large-Scale Networks, Proceedings of the International Conference on Database Systems for Advanced Applications (DASFAA), 404-421, 2017. Best Student Paper Award.
• VLDB Yubao Wu, Yuchen Bian, and Xiang Zhang. Remember Where You Came From: On the Second-Order Random Walk Based Proximity Measures, Proceedings of the International Conference on Very Large Data Bases (VLDB), 10(1):13-24, 2017.
• TKDE Yubao Wu, Ruoming Jin, and Xiang Zhang. Efficient and Exact Local Search for Random Walk Based Top-K Proximity Query in Large Graphs, IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(5): 1160-1174, 2016.
• TKDD Yubao Wu, Xiaofeng Zhu, Li Li, Wei Fan, Ruoming Jin, and Xiang Zhang. Mining Dual Networks: Models, Algorithms and Applications, ACM Transactions on Knowledge Discovery from Data (TKDD), 10(4):40, 2016.
• SIGMOD Yubao Wu, Ruoming Jin, and Xiang Zhang. Fast and Unified Local Search for Random Walk Based K-Nearest-Neighbor Query in Large Graphs, Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 1139-1150, 2014.

All Publications »

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Courses

• CSC4740/6740 Data Mining (Fall'16, Fall'18)
• CSC4760/6760 Big Data Programming (Spring'17, Spring'18, Spring'20)
• CSC8741 Graph Mining (Fall'17, Spring'19, Fall'20)

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Advising More »

• Ph.D. Students Xucan Chen, Xueting Liao, Fengpan Zhao
• Master Students Avinash Bondalapati, Meghana Kodali, Venkata Bharath Malapati, Sameera Turupu, Lakshmi Sravya Kambhampati

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Professional Service

Conference Committees

• Web Chair. The Smart World Congress 2021, Atlanta, Georgia.
• Program Committee Chair. The 7th IEEE International Conference on Internet of People (IoP) 2021, Atlanta, Georgia.
• Local Chair and Program Committee Member. The 2020 IEEE International Conference on Big Data, Atlanta, Georgia.
• Local Chair. The 12th International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage (SpaCCS) 2019, Atlanta, Georgia.
• Program Committee Member. The 13th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2018), Tianjin, China.

Journal Referee

• IEEE TKDE; ACM TKDD; Springer VLDB Journal