The latest version of the website: www.speedlab.network
Security, Privacy and intElligence for Edge Devices laboratory (SPEED Lab) is an interdisciplinary research group with a comprehensive mission. At its core, the lab is dedicated to develop distributed machine learning algorithms to facilitate cooperative decision-making for multi-agent systems. We strive to place significant emphasis on edge intelligence, tailoring the potential of decentralized computing to enable efficient decision-making. A central focus of our research is the pioneering of advanced techniques and protocols to safeguard users' data, particularly in the areas of federated learning, cybersecurity, and blockchain. With a wide-ranging focus that spans multiple domains, including computer vision, interdependent networks, and IoT, we are committed to delivering innovative solutions that address complex engineering applications and ensure the protection of user data, making valuable contributions to the ever-evolving landscape of distributed networks.
Announcements: A fully funded Ph.D. position is available! We are looking for strongly motivated candidates having experience in Computer Vision, Federated Learning or Cybersecurity.
General research topics include:
Federated Learning
Computer Vision
Interdependent Networks
Cybersecurity
IoT
Blockchain
Ongoing Research
Preventing Cybersecurity Threats in a Highly Malicious Distributed Machine Learning based IoT Environment
Project aim: Detect data poisoning and model poisoning attacks and guarantee convergence by tackling malicious participants within an FL environment.
Towards a Lightweight and Scalable Blockchain Framework for Resource-Constrained Federated Learning (FL) Environment
Project aim: Develop a lightweight and scalable blockchain framework tailoring an effective blockchain consensus mechanism to circumvent malicious activities. The project has broader prospects in security, storage, and incentive mechanism.
Developing a Distributed Machine Learning (ML) Framework for Interdependent Cyber-Physical-Societal Networks
Project aim:
(1) Capture interdependence among human-centered multi-layer critical infrastructures;
(2) Perform data analytics and enable interdependent decision making; and
(3) Develop efficient solutions that are capable of finding globally optimum solutions.
Improving Resilience of Resource-Constrained Critical Infrastructures
Project aim:
(1) Facilitate training of each agent in a distributed fashion;
(2) Resource optimization in exchanging knowledge; and
(3) Minimal communication overhead during training.
Recent Highlights
[09/23] One paper is accepted at IEEE CNS'23, one of the premier conference on computer and network security!
[09/23] SPEED Lab MS student Saika Zaman has won the Second Prize at the at the ACM Student Research Competition (SRC) during the 2023 CMD-IT/ACM Richard Tapia Celebration of Diversity in Computing Conference for her research on Federated Learning. Congratulations, Saika!
[09/23] SPEED Lab PhD Student, Md Zarif Hossain has been awarded with prestigious NSF Student Travel Grant to attend 2023 ACM MobiHoc!
[09/23] Our paper on Federated Learning and Blockchain is accepted at IEEE Internet of Things Journal (Impact Factor: 10.238)!
[07/23] Our research paper is accepted at IEEE DSC'23!
[07/23] Dr. Imteaj serves on the Program Committee of AAAI'24!
[06/23] Our paper, Assessing Wearable Human Activity Recognition Systems Against Data Poisoning Attacks in Differentially-Private Federated Learning, has been accepted to IEEE SmartComp'23! SPEED Lab PhD student Md. Zarif Hossain presented the paper at Nashville, TN.
[05/23] Dr. Imteaj serves on the Technical Program Committee of the 2023 IEEE World AI IoT Congress.
[04/2023] SPEED Lab member, Saika Zaman has been accepted to present her paper at the 2023 CMD-IT/ACM Richard Tapia Celebration of Diversity in Computing Conference in Dallas, Texas, and she has been awarded the prestigious Tapia scholarship. Congratulations, Saika!
[03/2023] SPEED Lab Director, Dr. Imteaj and PhD Student, Zarif served as judges at the 2023 Science Fair held at SIUC.
[2/23] Our latest research in collaboration with RMU is accepted at IEEE Consumer Electronics Journal! [Impact Factor: 4.135]
[01/23] Our latest research entitled “A Novel Scalable Reconfiguration Model for the Post disaster Network Connectivity of Resilient Power Distribution Systems” in collaboration with FIU and University of Nottingham is published at Sensors Journal! [Impact Factor: 3.847] [Link]
[01/23] Dr. Imteaj is teaching Artificial Intelligence in spring'23 at SIUC!
[1/23] Dr. Imteaj joined as a Guest Editor of Privacy and Security in Federated Learning, A special issue of Journal of Surveillance, Security and Safety. [Link]
[11/22] Our latest research on Federated Learning has been accepted at the AI to Accelerate Science and Engineering, Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI'23)!
[10/22] Our latest research on Label Flipping Data Poisoning Attack Against Wearable Human Activity Recognition System with a collaboration with Robert Morris University is accepted at IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022)!
[09/22] Our recent research work entitled “Federated Learning for Resource-Constrained IoT Devices: Panoramas and State of the Art” in collaboration with researchers from FIU, Deep Learning Research at Samba Nova Systems, IBM TJ Watson, and Binghamton University is published in Federated and Transfer Learning Book!
[08/222] Dr. Imteaj is teaching Machine Learning & Soft Computing course in the SoC at SIUC during the Fall'22 semester!
[08/22] Dr. Imteaj joined as a Tenure-track Assistant Professor in the School of Computing at SIUC!
[08/22] Dr. Imteaj recognized as the "2022 Real Triumphs Graduate" in the FIU Summer-2022 Commencement Ceremony! [Link] [FIU KFSCIS Coverage] [FIU CEC Coverage]
[07/22] Dr. Imteaj received the GPSC Travel Grant for our accepted paper at the CSCE'22 conference!
[04/22] Dr. Imteaj received the “2022 Outstanding Student Life Award: the Graduate Scholar of the Year Award" from the Division of Academic and Student Affairs at FIU.
[12/21] Dr. Imteaj received “2021 Best Graduate Student Research Award" at the FIU Knight Foundation School of Computing and Information Sciences. [Link][Link]
[12/21] Dr. Imteaj received the “Outstanding Master's Degree Graduate” award from Florida International University. This award has been given to only one master's graduate among all the engineering and computing departments. [Link] [Link]
Our collaborative work with Deep Learning Research at Samba Nova Systems, IBM TJ Watson, and Binghamton University, entitled “A Survey on Federated Learning for Resource-Constrained IoT Devices” is accepted in IEEE Internet of Things Journal (Impact factor: 10.207)! (Download Link) (IEEE Link)
We were invited to the FIU Book Authors Recognition Ceremony for our recently published book entitled, "Foundations of Blockchain: Theory and Applications" which is published by Springer and now available on Amazon! [Link] [Link]
Our paper in collaboration with Texas A&M University at Galveston and Lehigh University, entitled, "FedResilience: A Federated Learning Application to Improve Resilience of Resource-Constrained Critical Infrastructures" is published in the Special Issue on “Security of Cyber-Physical Systems” at Electronics Journal! (Impact Factor: 2.397) [Link]
[12/21] Dr. Imteaj received the IHCI-2021 Travel Scholarship Award for his latest research paper, "Exploiting Federated Learning Technique to Recognize Human Activities in Resource-constrained Environment" at IHCI'21, Kent, Ohio! [Link]
[12/21] Conducted a presentation session as a Session Chair at ICMLA'21 conference!
Our research paper on Distributed Network Optimization for Secure Operation of Interdependent Complex Networks funded by ARFL is accepted in The 2021 International Conference on Computational Science and Computational Intelligence (CSCI'21) (Acceptance rate: 16%). Dr. Imteaj presented the paper.
Conducted a webinar on, "Distributed Machine Learning for Large-Scale Critical Infrastructure Resilience: Tale of Energy Systems" as an invited speaker in Commemoration of IEEE PES Day.
Dr. Imteaj joined the Editorial Board of Data Science for Communications as a Review Editor for Frontiers in Communications and Networks Journal.
