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Personal profile
University profile
Dr. Boxiang Dong is assistant professor in the Computer Science Department at Montclair State University. He received a Ph.D in Computer Science from Department of Computer Science of Stevens Institute of Technology.
His research interests fall into the intersection of cybersecurity and big data analytics. In particular, his research topics cover:
Applying deep learning in intrusion detection, financial fraud detection and weather forecast
Causal inference in environment change
Privacy-preserving and authenticated data computations
Research interests
Intersection of cybersecurity and big data analytics. In particular, his research topics cover:
Applying deep learning in intrusion detection, financial fraud detection and weather forecast
Causal inference in environment change
Privacy-preserving and authenticated data computations
Scholarly Interests
Machine learning and cybersecurity
Faculty/Media Expert
Expert on intrusion detection, financial risk analysis, verifiable computation, and privacy-preserving data mining.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Projects
- 1 Active
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CorrectMR: Authentication of Distributed SQL Execution on MapReduce
Zhang, B., Dong, B. & Wang, W. H., 1 Mar 2021, In: IEEE Transactions on Knowledge and Data Engineering. 33, 3, p. 897-908 12 p., 8807323.Research output: Contribution to journal › Article › peer-review
3 Scopus citations -
Integrity Authentication for SQL Query Evaluation on Outsourced Databases: A Survey
Zhang, B., Dong, B. & Wang, W. H., 1 Apr 2021, In: IEEE Transactions on Knowledge and Data Engineering. 33, 4, p. 1601-1618 18 p., 8868216.Research output: Contribution to journal › Review article › peer-review
2 Scopus citations -
Towards Trustworthy Outsourced Deep Neural Networks
Ahmad, L., Dong, B., Samanthula, B., Wang, R. Y. & Li, B. H., 2021, Proceedings - 2021 IEEE Cloud Summit, Cloud Summit 2021. Institute of Electrical and Electronics Engineers Inc., p. 83-88 6 p. (Proceedings - 2021 IEEE Cloud Summit, Cloud Summit 2021).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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VDGAN: A Collaborative Filtering Framework Based on Variational Denoising with GANs
Sun, W., Yu, S. & Dong, B., 18 Jul 2021, IJCNN 2021 - International Joint Conference on Neural Networks, Proceedings. Institute of Electrical and Electronics Engineers Inc., (Proceedings of the International Joint Conference on Neural Networks; vol. 2021-July).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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VeriDL: Integrity Verification of Outsourced Deep Learning Services
Dong, B., Zhang, B. & Wang, H., 2021, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Proceedings. Oliver, N., Pérez-Cruz, F., Kramer, S., Read, J. & Lozano, J. A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 583-598 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12976 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
1 Scopus citations