Intelligent and Sustainable Edge Computing (I-SEC) Lab

At the Intelligent and Sustainable Edge Computing (I-SEC) Laboratory, led by Dr. Yu Chen, Professor of Electrical and Computer Engineering, we are at the forefront of pioneering the next generation of intelligent Internet of Things (IoT) technologies. Our research is centered around Trust, Security, and Privacy within the Edge-Fog-Cloud Computing paradigm, specifically focusing on the IoT and its applications in creating intelligent and interconnected environments.

Currently, we focus on:

Secure-by-design IoT ecosystem atop a customized lightweight Blockchain network
Immersive and interconnected 3D edge-fog computing paradigms
Detecting, deterring, and mitigating misinformation, disinformation, and malinformation
Digital Twins and IoMT-enabled digital healthcare services (DHS)

Recent Updates

Jan 2, 2024	Congratulations Dr. Chen has been elected to the grade of Fellow of SPIE!
Dec 27, 2023	Congratulations Simeon successfully passed the comprehensive exam!
Dec 5, 2023	Dr. Chen gave a keynote talk, “Securing Truth: Technology’s Role in Fighting Misinformation on Social Media” at the 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2023), National Telecommunication Institute (NTI) – Smart Village, Giza, Egypt, Dec. 4-7, 2023. [Slides]
Oct 10, 2023	Dr. Chen is on Stanford University’s list of the World’s 2% Top Cited Scientists! This is the 2nd year Dr. Chen is listed for both career-long and single-year impacts in the subfield of Information and Communication Technologies.

Selected Publications

DeFake: Decentralized ENF-Consensus Based DeepFake Detection in Video Conferencing

Deeraj Nagothu, Ronghua Xu, Yu Chen, and 2 more authors

In IEEE 23rd International Workshop on Multimedia Signal Processing Oct 2021
DeFakePro: Decentralized Deepfake Attacks Detection Using ENF Authentication

Deeraj Nagothu, Ronghua Xu, Yu Chen, and 2 more authors

IT Professional Sep 2022

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Advancements in generative models, such as deepfake, allow users to imitate a targeted person and manipulate online interactions. It has been recognized that disinformation may cause disturbance in society and ruin the foundation of trust. This article presents DeFakePro, a decentralized consensus mechanism-based deepfake detection technique in online video conferencing tools. Leveraging electrical network frequency (ENF), an environmental fingerprint embedded in digital media recording affords a consensus mechanism design called proof-of-ENF (PoENF) algorithm. The similarity in ENF signal fluctuations is utilized in the PoENF algorithm to authenticate the media broadcasted in conferencing tools. By utilizing the video conferencing setup with malicious participants to broadcast deepfake video recordings to other participants, the DeFakePro system verifies the authenticity of the incoming media in both audio and video channels.
uDFL: A Secure Microchained Decentralized Federated Learning Fabric atop IoT Networks

Ronghua Xu, and Yu Chen

IEEE Transactions on Network and Service Management Sep 2022
Microchain: A Light Hierarchical Consensus Protocol for IoT Systems

Ronghua Xu, Yu Chen, and Erik Blasch

Sep 2021
Robustness of Electrical Network Frequency Signals as a Fingerprint for Digital Media Authentication

Nihal Poredi, Deeraj Nagothu, Yu Chen, and 4 more authors

In 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP) Sep 2022

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Real-time human detection as an edge service enabled by a lightweight cnn

Seyed Yahya Nikouei, Yu Chen, Sejun Song, and 3 more authors

In 2018 IEEE International Conference on Edge Computing (EDGE) Sep 2018