Ph.D. Student (Expected Fall 2023),
University of Houston
Graduate Teaching Assistant (Jan 2022 - Present)
Graduate Research Assistant (Sep 2019 - Dec 2021)
Major: Computer and Information Science
Concentration: Cyber Security
Lab: Networked Systems Laboratory (2022-present), Resilient Networks and Systems (RNS) Lab (2019-present)
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I have been working as a Teaching/Research Assistant after joining as a Ph.D. student at the Department of Computer Science, the University of Houston since Fall-2019. My primary research interest is in Cyber Deception, IoT Security, Privacy, Data Analytics & ML, and the Cloud-IoT ecosystem. I started my journey in the research arena in 2016 and have been publishing my ideas and works since then.
Currently, I am researching Cyber Deception and Adversarial Reconnaissance. Now, we are working on modeling attacker behavior inside a compromised network. In another project, I have been working on IoT Remote Attestation where we have built an IoT testbed for researching software vulnerabilities, exploitation, and attestation techniques such as memory checksum, CFI, etc. We have presented the first game-theoretic analysis of remote attestation and now we are working on a multiagent learning-based model.
Before joining UH, I worked as a lecturer in the Dept. of CSE, Green University of Bangladesh. I like to collaborate with other researchers, and together we have been working on projects and publications. I also like to have hands-on experiences in System Administration, which made me take part in RHCSA, RHCE, Openstack, CCNA, etc vendor courses, and exams. I intend to gather more knowledge that covers the topics of DevSecOps.
News & Updates
I am going to attend my Ph.D. Proposal Defense in November of 2022.
I joined the Networked Systems Laboratory of Dr. Omprakash Gnawali in the Fall of 2022. I will also remain a part of the Resilient Network and Systems Lab (Dr. Aron Laszka).
Our paper entitled "DARSH: Deceiving Adversaries through Redirection to Semi-Indistinguishable Honeypot Web Servers" has been submitted to a conference for review. This work is collaborative among the University of Houston, the University of Texas at El Passo, and the DEVCOM Army Research Laboratory.
Our paper entitled "Survey and Taxonomy of Adversarial Reconnaissance Techniques" has been accepted in the ACM Computing Surveys. [2020 Impact Factor: 10.282 (ranked 4/137 in Computer Science Theory & Methods)] This work is part of projects: National Science Foundation under Grant CNS1850510 and the Army Research Office under Award W911NF-17-1-0370. It is a collaborative work among the University of Houston, the University of Texas at El Passo, and the DEVCOM Army Research Laboratory.
I am going to serve as a Technical Program Committee member of the International Conference on Machine Intelligence and Emerging Technologies (MIET 2022)
I presented our paper entitled "Strategic Remote Attestation: Testbed for Internet-of-Things Devices and Stackelberg Security Game for Optimal Strategies" at the 2021 Conference on Decision and Game Theory for Security.
Our paper entitled "Strategic Remote Attestation: Testbed for Internet-of-Things Devices and Stackelberg Security Game for Optimal Strategies" has been accepted at the 2021 Conference on Decision and Game Theory for Security. The work was supported by the National Science Foundation under Grant No. CNS-1850510, IIS-1905558, and ECCS-2020289 and by the Army Research Office under Grant No. W911NF1910241 and W911NF1810208.
I started a new GitHub Repository entitled CyberSecurity Concepts in Python to provide different security concepts in Python. Blog Posts are also available alongside codes. Please find the links in the README.md file. Find more posts on shantoroy.com.
I presented our work in progress (WIP Paper) entitled "WiP: Strategic Remote Attestation: Testbed for Internet-of-Things Devices and Stackelberg Security Game for Optimal Strategies" in the Hot Topics in the Science of Security, 2021.
Our paper entitled "A Privacy-preserving Mobile and Fog Computing Framework to Trace and Prevent COVID-19 Community Transmission" has been published in the IEEE Journal of Biomedical and Health Informatics. This work is part of the Australian Research Council Grant ID: DP190100314 and collaboration among the Queensland University of Technology, the University of Houston, and the University of Melbourne.