Vir V. Phoha


Electrical Engineering and Computer Science

4-183 CST



  • Ph.D. Texas Tech University

Research Interests:

  • Cyber Security – Cyber offense and defense
  • Machine Learning
  • Smart phones and tablets security
  • Biometrics — network based and standalone

Current Research:

My focus is to do original research that cuts across conventional rigorously defined disciplines and unifies basic and common concepts across disciplines. In particular, my research centers around security (malignant systems, active authentication, for example touch based authentication on mobile devices) and machine learning (decision trees, statistical, and evolutionary methods) with a focus on large time series data streams and static data sets, and computer networks (anomalies, optimization). I am also using these methods to build field realizable defensive and offensive Cyber-based systems. 

Courses Taught:

  • Security and Machine learning; Biometrics
  • Applied Cryptography

Honors and Awards:

  • Fellow of: AAAS; AAIA; IEEE; NAI; SDPS 
  • ACM Distinguished Scientist 
  • IEEE Computer Society Distinguished Visitor (2024-2026) 
  • ACM Distinguished Speaker (2012-2015) 
  • IEEE Region 1 Technological Innovation  Award, 2017 

Selected Publications:

  • F. Chen, J. Xin and V. V. Phoha, “SSPRA: A Robust Approach to Continuous Authentication Amidst Real-World Adversarial Challenges,” in IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 6, no. 2, pp. 245-260, April 2024, doi: 10.1109/TBIOM.2024.3369590 
  • Jingyu Xin, Vir V. Phoha, and Asif Salekin. 2022. Combating False Data Injection Attacks on Human-Centric Sensing Applications. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 2, Article 83 (July 2022), 22 pages. 
  • Xinyi Zhou, Kai Shu, Vir V. Phoha, Huan Liu, and Reza Zafarani. 2022. “This is Fake! Shared it by Mistake”:Assessing the Intent of Fake News Spreaders. In Proceedings of the ACM Web Conference 2022 (WWW ’22). Association for Computing Machinery, New York, NY, USA, 3685–3694. 
  • Fallahi, A., Phoha, V.V. (2021). Adversarial Activity Detection Using Keystroke Acoustics. In: Bertino, E., Shulman, H., Waidner, M. (eds) Computer Security – ESORICS 2021. ESORICS 2021. Lecture Notes in Computer Science(), vol 12972. Springer, Cham. 
  • Xinyi Zhou, Atishay Jain, Vir V. Phoha, and Reza Zafarani. 2020. Fake News Early Detection: A Theory-driven Model. ACM Digital Threats 1, 2, Article 12 (June 2020), 25 pages. 
  • B. Li, W. Wang, Y. Gao, V. V. Phoha and Z. Jin, “Wrist in Motion: A Seamless Context-Aware Continuous Authentication Framework Using Your Clickings and Typings,” in IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 2, no. 3, pp. 294-307, July 2020, doi: 10.1109/TBIOM.2020.2997004.