Publications

Extracting Threat Intelligence From Cheat Binaries For Anti-Cheating

Published in Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses, 2023

Rampant cheating in games drives developers to seek solutions, leading to the creation of CheatFighter, an automated system that extracts intelligence from cheat binaries to randomize data, effectively countering 80 out of 86 real-world cheats in under a minute for Android and Windows games.

Recommended citation: Md Sakib Anwar, Chaoshun Zuo, Carter Yagemann, and Zhiqiang Lin. 2023. Extracting Threat Intelligence From Cheat Binaries For Anti-Cheating. In Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses (RAID 23). Association for Computing Machinery, New York, NY, USA, 17-31. https://doi.org/10.1145/3607199.3607211
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A comparative study on Gaussian process regression-based indoor positioning systems

Published in 2018 International Conference on Innovation in Engineering and Technology (ICIET), 2018

Gaussian Process Regression (GPR) is highly accurate for predicting online radio maps in fingerprinting-based localization, but its accuracy depends on the mean function used; this paper compares various Indoor Positioning Systems (IPS) with GPR mean functions and introduces two new neural network-based mean functions that outperform traditional ones.

Recommended citation: M. S. Anwar, F. Hossain, N. Mehajabin, M. Mamun-Or-Rashid and M. A. Razzaque, "A Comparative Study on Gaussian Process Regression-based Indoor Positioning Systems," 2018 International Conference on Innovation in Engineering and Technology (ICIET), Dhaka, Bangladesh, 2018, pp. 1-5, doi: 10.1109/CIET.2018.8660860. keywords: {Ground penetrating radar;Artificial neural networks;Predictive models;Gaussian processes;IP networks;Data models;Indoor Positioning System;Gaussian Process Regression;Neural Network;Fingerprinting},
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