Posts by Collection

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},
Download Paper

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
Download Paper | Download Slides

GoSonar: Detecting Logical Vulnerabilities in Memory Safe Language Using Inductive Constraint Reasoning

Published in 46th IEEE Symposium on Security and Privacy, 2025

Inductive constraint reasoning is proposed to evaluate nontermination in Go programs, revealing five new vulnerabilities in the Go standard library.

Recommended citation: M. S. Anwar, C. Yagemann and Z. Lin, "GoSonar: Detecting Logical Vulnerabilities in Memory Safe Language Using Inductive Constraint Reasoning," in 2025 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA, 2025, pp. 43-43, doi: 10.1109/SP61157.2025.00043.
Download Paper | View on GitHub | View on Docker Hub

SP’21 TA for CSE 1222

Undergraduate Course, The Ohio State University, CSE, 2021

As a Teaching Assistant for CSE 1222: Introduction to C++ Programming, I enhanced students’ learning experiences by conducting interactive lab sessions, demonstrating coding techniques, and providing hands-on guidance through exercises and projects. Specifically, being online helping students create an environment that they can be productive in was essential.

AU’21 TA for CSE 1222

Undergraduate Course, The Ohio State University, CSE, 2021

As a Teaching Assistant for CSE 1222: Introduction to C++ Programming, I enhanced students’ learning experiences by conducting interactive lab sessions, demonstrating coding techniques, and providing hands-on guidance through exercises and projects. I also managed a team of graders, ensuring timely and fair assessment of student work, and assisted in grading exams.