Research

Research Grants

  • Security Evaluation and Improvement of the Personal Cyberinfrastructure with New Tools and Education Development, CRDF Global, Role: Co-PI (PI: Leon Reznik, from Rochester Institute of Technology), Funding: $74,995.59, Project Duration: 1 year (2021 - 2022)
  • CyberTraining: Implementation: Small: Using Problem-Based Learning for Vocational Training in Cyberinfrastructure Security at Community Colleges, National Science Foundation (NSF) - Training-based Workforce Development for Advanced Cyberinfrastructure (CyberTraining), Role: PI (PI: Irfan Ahmed from Virginia Commonwealth University), Funding: $499,661, Project Duration: 3 years (2020 - 2023)
  • Identifying Best DDoS Protection Practices for Power Utility Practitioners, Protect Our Power, Role: PI, Funding: $25,000, Project Duration: 0.5 year (2020 - 2021)
  • Instructional Material for SCADA Security Course, National Security Agency (NSA), Role: Co-PI (PI: Irfan Ahmed and Co-PI: Vassil Roussev from University of New Orleans), Funding: $187,964, Project Duration: 1 year (2017 - 2018)

Research Areas & Recent Publications

The Cybersecurity and Privacy Center (CyPC) at Sacred Heart University has several ongoing research projects broadly divided into ML/AI & cybersecurity, data privacy & security, cybersecurity education and CPS/ICS security. These projects have resulted in several research papers that have been published in peer-reviewed and high-impact journals and conferences.

ML/AI & Cybersecurity

  • Mohanan, S., Sridhar, N., & Bhatia, S. (2022). Comparative Analysis of Cloud Computing Security Frameworks for Financial Sector. In Proceedings of Sixth International Congress on Information and Communication Technology (pp. 1015–1025).
  • Razaque, A., Amsaad, F., Halder, D., Baza, M., Aboshgifa, A., & Bhatia, S. (2021). Analysis of Sentimental Behaviour over Social Data Using Machine Learning Algorithms. In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (pp. 396–412).
  • Mohanan, S., Sridhar, N., & Bhatia, S. (2022). Comparative Analysis of Cloud Computing Security Frameworks for Financial Sector. In Proceedings of Sixth International Congress on Information and Communication Technology (pp. 1015–1025).
  • Ghazal, R., Malik, A., Raza, B., Qadeer, N., Qamar, N., & Bhatia, S. (2021). Agent-Based Semantic Role Mining for Intelligent Access Control in Multi-Domain Collaborative Applications of Smart Cities. Sensors, 21(13), 4253.
  • Khokhlov, I., Reznik, L., & Chuprov, S. (2020). Framework for integral data quality and security evaluation in smartphones. IEEE Systems Journal.
  • Khokhlov, I., & Reznik, L. (2020). What is the value of data value in practical security applications. In 2020 IEEE Systems Security Symposium (SSS) (pp. 1–8).
  • Saini, P., Behal, S., & Bhatia, S. (2020). Detection of DDoS attacks using Machine Learning algorithms. In 2020 7th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 16–21).
  • Khokhlov, I., Li, Q., & Reznik, L. (2019). Difense: Distributed intelligent framework for expendable android security evaluation. In The 14th Annual Symposium on Information Assurance (ASIA’19) (pp. 18–27).

Data Privacy & Security

  • Khokhlov, I., Ligade, N., & Reznik, L. (2020). Recurrent neural networks for colluded applications attack detection in android os devices. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1–8).
  • Daniels, J., & Bhatia, S. (2020). Legislation and the Negative Impact on Cybersecurity in Healthcare. In 6th International Conference on Information Systems Security and Privacy.
  • Khokhlov, I., Perez, M., & Reznik, L. (2019). Machine learning in anomaly detection: Example of colluded applications attack in android devices. In 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA) (pp. 1328–1333).
  • Khokhlov, I., Perez, M., & Reznik, L. (2019). System signals monitoring and processing for colluded application attacks detection in android os. In 2019 IEEE Western New York Image and Signal Processing Workshop (WNYISPW) (pp. 1–5).

Cybersecurity Education

  • Bhatia, S., Bhatia, S., & Ahmed, I. (2022). Automated Waterloo Rubric for Concept Map Grading. In IEEE Access (accepted).
  • Nguyen, T., & Bhatia, S. (2020). Higher Education Social Engineering Attack Scenario, Awareness & Training Model. In Journal of The Colloquium for Information Systems Security Education (pp. 8–8).
  • Shivapurkar, M., Bhatia, S., & Ahmed, I. (2020). Problem-based Learning for Cybersecurity Education. In Journal of The Colloquium for Information Systems Security Education (pp. 6–6).
  • Mountrouidou, X., Vosen, D., Kari, C., Azhar, M., Bhatia, S., Gagne, G., Maguire, J., Tudor, L., & Yuen, T. (2019). Securing the human: a review of literature on broadening diversity in cybersecurity education. Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education, 157–176.
  • Azhar, M., Bhatia, S., Gagne, G., Kari, C., Maguire, J., Mountrouidou, X., Tudor, L., Vosen, D., & Yuen, T. (2019). Securing the human: Broadening diversity in cybersecurity. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education (pp. 251–252).

CPS/ICS Security

  • Saxena, S., Bhatia, S., & Gupta, R. (2021). Cybersecurity Analysis of Load Frequency Control in Power Systems: A Survey. Designs, 5(3), 52.
  • Amsaad, F., Razaque, A., Baza, M., Kose, S., Bhatia, S., & Srivastava, G. (2021). An efficient and reliable lightweight PUF for IoT-based applications. In 2021 IEEE international conference on communications workshops (ICC Workshops) (pp. 1–6).
  • Parian, C., Guldimann, T., & Bhatia, S. (2020). Fooling the Master: Exploiting Weaknesses in the Modbus Protocol. Procedia Computer Science, 171, 2453–2458.
  • Lakew Yihunie F., Singh A.K., Bhatia S. (2020). Assessing and Exploiting Security Vulnerabilities of Unmanned Aerial Vehicles, In 2020 Smart Systems and IoT: Innovations in Computing (pp. 701–710).