Bhavani Thuraisingham is a Professor of Computer Science, Executive Director of the Cyber Security Research and Education Institute and the Louis A. Beecherl Jr. Distinguished Professor. Her research interests include:

  • Data Security
  • Data Mining for Counter-Terrorism
  • Secure Cloud Computing
  • Assured Information Sharing
  • Surveillance/Biometrics
  • Cyber Security
  • Privacy


Awarded the 2019 Communications and Information Security Technical Recognition Award from the Institute of Electrical and Electronics Engineers (IEEE) Communications Society.

Works in Treasures @ UT Dallas are made available exclusively for educational purposes such as research or instruction. Literary rights, including copyright for published works held by the creator(s) or their heirs, or other third parties may apply. All rights are reserved unless otherwise indicated by the copyright owner(s).

Recent Submissions

  • Specification and Analysis of ABAC Policies via the Category-Based Metamodel 

    Fernandez, Maribel; Mackie, Ian; Thuraisingham, Bhavani (Assoc Computing Machinery, 2019-03-25)
    The Attribute-Based Access Control (ABAC) model is one of the most powerful access control models in use. It subsumes popular models, such as the Role-Based Access Control (RBAC) model, and can also enforce dynamic policies ...
  • Multistream Classification for Cyber Threat Data with Heterogeneous Feature Space 

    Li, Yifan; Tao, Hemeng; Gao, Yang; Khan, Latifur; Ayoade, Gbadebo; Thuraisingham, B. (Association for Computing Machinery, Inc, 2019-05)
    Under a newly introduced setting of multistream classification, two data streams are involved, which are referred to as source and target streams. The source stream continuously generates data instances from a certain ...
  • Towards Self-Adaptive Metric Learning on the Fly 

    Gao, Yang; Li, Yi-Fan; Chandra, Swarup; Khan, Latifur; Thuraisingham, Bhavani (Association For Computing Machinery, Inc, 2019-05)
    Good quality similarity metrics can significantly facilitate the performance of many large-scale, real-world applications. Existing studies have proposed various solutions to learn a Mahalanobis or bilinear metric in an ...
  • Towards a Privacy-Aware Quantified Self Data Management Framework 

    Thuraisingham, Bhavani M.; Kantarcioglu, Murat; Bertino, E.; Bakdash, Jonathan Z.; Fernandez, M.
    Massive amounts of data are being collected, stored, and analyzed for various business and marketing purposes. While such data analysis is critical for many applications, it could also violate the privacy of individuals. ...
  • Integrating Cyber Security and Data Science for Social Media: A Position Paper 

    Thuraisingham, Bhavani M.; Kantarcioglu, Murat; Khan, Latifur
    Cyber security and data science are two of the fastest growing fields in Computer Science and more recently they are being integrated for various applications. This position paper will review the developments in applying ...
  • Large-Scale Realistic Network Data Generation on a Budget 

    Ricks, Brian; Tague, P.; Thuraisingham, Bhavani M.
    Many novel problems in computer networking require relevant network trace data during the research process. Unfortunately, such data can often be hard to find, which becomes a problem within itself. While generating ...