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Contact

  • Address:
    • Alex Hai Wang
    212A Dawson Bldg.
    120 Ridge View Drive
    Dunmore, PA 18512
  • Phone:
    • 570-963-2559 (office)
    570-218-WANG
  • Email:
    • hwang@psu.edu

Research Interests

  • Information Security and Privacy
  • Security and Privacy in Social Networks
  • Cloud Computing
  • Machine Learning and Data Mining
  • Database Security
  • Survivability Modeling and Evaluation

    • Professional Services

  • Editorial Board Member, International Journal of Information Technology and Engineering
  • Program Committee Member, 2011 International Conference on Emerging Security Information, Systems and Technologies (SECURWARE 2011)

    • Research Projects

  • Security and Privacy in Social Networks:

    • Online social networking sites, such as Twitter, Facebook, and LinkedIN, are one of the most popular applications of Web 2.0. The goal of online social networking sites is to allow friends communicate and stay connected. Unfortunately, spammers also use social networks as a tool to post malicious links, send unsolicited messages to legitimate users. This project focuses on detecting spam on Twitter using machine learning approaches.

  • Survivability Modeling and Evaluation:

    • The goal of this project is to develop a survivability evaluation model that can systematically address the inherent limitations of classic availability evaluation models in measuring survivability. Quantitative measures are expected to characterize the capability of a resilient system surviving intrusions. Furthermore, we are interested in understanding the impact of existing system deficiencies and attack behaviors on the survivability.

  • Self-Protecting Data Centers:

    • Virtual machine based services are becoming predominant in data centers or cloud computing. While there are many promising security techniques based on virtual machines, it is not clear how significant the difference between various system architectures can be in term of survivability. In this research, we analyze the survivability of various virtual machine based architectures. The results show that even if the same set of software is used, the performance of various service architectures is largely different in surviving attacks.

    Collaborators

  • Peng Liu @ Penn State
  • Chao-Hsien Chu @ Penn State
  • Meng Yu @ Virginia Commonwealth University
  • Wanyu Zang @ Western Illinois University
  • Qijun Gu @ Texas State
  • Kun Bai @ IBM T.J. Watson Research Center
  • Su Yan @ IBM Almaden Research Center