RESEARCH

Dr. Alam is leading the Fordham Dependable and Secure System Lab ( DependSys Lab) with a research group at the Fordham University.

GRADUATE STUDENTS/POSTDOCS
  • Movses Musaelian, E-Government in a Data-Driven World: A Survey [2018-Present]
  • Revathi Bhuvaneswari, Banking/Finance industries handle sensitive customer data [2018-Present]
  • Megha Anand, Security Performance in Embedded IoT devices [2018-Present]
  • Simran Sidhu, Wi-Fi Signal collection and Security [2018-Present]
  • Michael Furman, Multimedia Data Security Analytics [2018-Present]
CO-SUPERVISED PHD STUDENTS
  • Faizan Khan,Wi-Fi Signal Applications [2016-Present]
  • Hafizur Rahman, Trustworthy Data Collection [2017-Present]
UNDERGRADUATE STUDENT
  • Md Monirul Islam, Application-Specific Wi-Fi Signal data mining and Security
  • Faiza Khan, Wi-Fi Signal Collection and Security Analysis
  • Mohaib Siddiqui, Privacy with Blockchain
STUDENTS GRADUATED
  • Aliuz Zaman, Anomaly Attack Detection, (2016- 2018)
  • Athina Rosales, Driving Anomaly Detection [2016-2018]
  • Muhammed Tanim Khan, Click Fraud and Attack Detection (2016–2018)

Ongoing Project:

  • Project Title: Trustworthy and Protected Data Collection

Project Theme: As the data collection becomes broader and easier through automated data collection, sensors, and the IoT, protecting the data is becoming more of a focus. The concept of “big data” just increases the focus. Many of the contributions to this focus is on maintaining data security and privacy in the process, storage, transmission, and decision-making. However, there can be a question, what would be the situation if low-quality, untrustworthy, meaningless, or undependable data are collected at the time of acquisition, and we apply various strong security protocols to process, store, and transmit the data and make decisions for various cyber applications. Also, what would be the situation when existing privacy-preserving protocols for communication and decision-making can be effective but to what value if the data being project are themselves suspect due to attacks on the privacy at the data gathering process. In this project, we will highlight these situations and show how untrustworthy concerns may appear during the data collection. We will then discuss challenges and potential solutions for the trustworthy data collection. The outcome of this project is to offer a trustworthy data collection for aggregation in decision-making for various network and CPS applications.

Publication:
  1. Entao Luo, Md Zakirul Alam Bhuiyan*, Guojun Wang, Md Arafatur Rahman, Jie Wu, and Mohammed Atiquzzaman,  “PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-based Healthcare Systems,”   IEEE Communication Magazine (COMMAG), 56(2): 163-168, 2018
  2. Md Zakirul Alam Bhuiyan and Jie Wu, “Trustworthy and Protected Data Collection for Event Detection Using Networked Sensing Systems,” The 37th IEEE Sarnoff Symposium 2016, Newark, New Jersey, USA, Sept 19-21, 2016
  3. Md Zakirul Alam Bhuiyan and Jie Wu, “Trustworthy and Protected Data Collection for Event Detection Using Networked Sensing Systems,” The 37th IEEE Sarnoff Symposium 2016, Newark, New Jersey, USA, Sept 19-21, 2016
  4. Md Zakirul Alam Bhuiyan, Guojun Wang, and Kim-Kwang Raymond Choo, “Secured Data Collection for a Cloud-Enabled Structural Health Monitoring System,” The 18th IEEE International Conference On High Performance Computing and Communications (IEEE HPCC), 12-14 December, 2016, Sydney, Australia
  5. Md Zakirul Alam Bhuiyan and Jie Wu, “Trustworthy and Protected Data Collection for Event Detection Using Networked Sensing Systems,” The 37th IEEE Sarnoff Symposium 2016, Newark, New Jersey, USA, Sept 19-21, 2016
  6. Hai Tao, Md Zakirul Alam Bhuiyan, Ahmed N. Abdalla, Mohammad Mehedi Hassan, Jasni Mohamad Zain Thaier Hayajneh, “Secured Data Collection with Hardware-based Ciphers for IoT-based Healthcare,” IEEE Internet of Things Journal (IEEE IoT-J), 2018 (under review)
  • Project Title: High-Quality Data Collection

Project Theme: Applying wireless vibration sensor networks (WVSNs) to this class is challenging due to severe resource constraints (e.g., bandwidth and energy). State-of-the-art data reduction approaches (e.g., signal processing, in-network aggregation) suggested to improve these constraints do not satisfy application-specific requirements, e.g., high quality of data (QoD) collection or quality of monitoring (QoM). In this project, we work on data collection, a general approach to vibration data collection and monitoring in a resource-constrained WVSN. We enable each sensor to reduce the amount of data (before transmission) in a decentralized manner in two stages: the data acquisition stage and data transmission stage. The outcome of this project is to offer a high-quality data collection for high-quality decision-making in various network and CPS applications.

Publication:
  1. Md Zakirul Alam Bhuiyan, Jie Wu, Guojun Wang, Zhigang Chen, Jianer Chen, and Tian Wang, “Quality-Guaranteed and Event-Senstive Data Collection and Monitoring in Wireless Vibration Sensor Networks,” IEEE Transactions on Industrial Informatics, 13(2): 572-583, April 2017 [SCI IF: 6.76, JCR Q1]
  2. Tian Wang, Yang Li, Guojun Wang, Jiannong Cao, Md Zakirul Alam Bhuiyan, Weijia Jia, “Sustainable and Efficient Data Collection from WSNs to Cloud”,  IEEE Transactions on sustainable computing (TSUSC), 2017, DOI: https://doi.org/10.1109/TSUSC.2017.2690301
  3. M. Z. A. Bhuiyan, Guojun Wang, Jiannong Cao, and Jie Wu, ” Vibration Data Collection and Monitoring in Wireless Sensor Networks,” Technical Report, Central South University, 2013 (Best Paper Award).
  4. Md Zakirul Alam Bhuiyan Guojun Wang, Jie Wu, Tian Wang, and Xiangyong Liu, “Resource-Efficient Vibration Data Collection in Cyber-Physical Systems,” Proceedings of the 15th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2015), Zhangjiajie, China, November 18-20, 2015
  5. Md Zakirul Alam Bhuiyan, Mdaliuz Zaman, Guojun Wang, Tian Wang, and Jie Wu, “Privacy-Protected Data Collection in Wireless Medical Sensor Networks,” The 12th International Conference on Networking, Architect and Storage (IEEE NAS 2017) will be held from August 7- 8, 2017 at Shenzhen, China