Enhancing Mobile Multimedia Trustworthiness through Federated AI-based Content Authentication: Enhancing Mobile Multimedia

Authors

  • M. Rajesh Department of Computer Engineering, Sanjivani College of Engineering, India
  • K. Vengatesan Department of Computer Engineering, Sanjivani College of Engineering, India
  • R. Sitharthan Centre for Smart Grid Technologies, School of Electrical Engineering, Vellore Institute of Technology, Chennai, India
  • Shanmuga Sundar Dhanabalan Functional Materials and Microsystems Research Group, RMIT University, Melbourne, Victoria 3001, Australia
  • Mahendra Bhatu Gawali Department of Information Technology, Sanjivani College of Engineering, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1963

Keywords:

Federated AI, Mobile Multimedia, Trustworthiness, Content Authentication

Abstract

The rapid proliferation of mobile devices and multimedia content has led to an increased need for ensuring trustworthiness and authentication of the shared data. Traditional centralized methods have proven to be insufficient in maintaining privacy and addressing scalability issues. This paper presents a novel approach to enhancing mobile multimedia trustworthiness through the application of Federated AI-based content authentication techniques. By leveraging the benefits of distributed machine learning and edge computing, our proposed framework efficiently authenticates multimedia data while preserving user privacy and reducing latency. Our system employs a federated learning model that trains AI algorithms on local devices, allowing them to collaboratively build a robust and accurate authentication model. Additionally, this research introduces a blockchain-based decentralized trust management system to further enhance the integrity and traceability of the authentication process. Through extensive evaluations, this research demonstrate that our proposed framework significantly improves the trustworthiness of mobile multimedia content while minimizing the overhead and resource consumption associated with traditional centralized approaches.

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Author Biographies

M. Rajesh, Department of Computer Engineering, Sanjivani College of Engineering, India

M. Rajesh is a highly motivated and experienced computer science professor with 15 years of teaching experience. He holds a PhD in Computer Science from St. Peter’s University, Chennai and a Master of Engineering in Computer Science and Engineering from Arunai College of Engineering, Thiruvannamalai. He began his career as a lecturer at Thiruvalluvar College of Engineering and Technology and later worked as a lecturer and assistant professor at KRS College of Engineering before joining Sanjivani College of Engineering as a Professor. He has a proven track record of research and publications in top-tier academic journals and conferences. He has published over 190 papers in international refereed journals like IEEE, Springer, and Elsevier and served as a reviewer for Springer, Inderscience, and Elsevier journals. He has also served as general chair for international and national conferences organized globally. He is an associate editor of IET Nanobiotechnology, IEEE Instrumentation & Measurement Magazine, IEEE Transactions on Industrial Informatics, Cluster Computing, 3D-Research (Springer) and editor of Mathematical and Computational Forestry, and Natural-Resource Sciences (MCFNS), International Journal of Sensors, Wireless Communications and Control, Wireless Communications and Mobile Computing (Hindawi). He has also served as PC members for many conferences conducted in India and abroad and also has successfully organized some special issues in highly indexed journals. In his current role at Sanjivani College of Engineering, Dr. Manoharan has dealing with funding proposals, organized and edited international conferences, and published numerous research articles. His main research interests include IoT, blockchain techniques, e-health technologies, and soft computing technique.

K. Vengatesan, Department of Computer Engineering, Sanjivani College of Engineering, India

K. Vengatesan currently working as Professor at Department of Computer Engineering, Sanjivani College of Engineering, 17 years of teaching experience in computer science engineering. He received a Ph.D. Computer Science and Engineering, SSSUTMS, Bhopal, Pursued M.Tech in Information Technology (2008–2010) from Sathyabama University, Chennai, and B.E. in Computer Science Engineering (2001–2005) in PGP College of Engineering And Technology (Anna University Chennai) Namakkal. His research area is in Data Analytics, Data mining, clustering, Life Time Member of Indian Society for Technical Education. Reviewer following journals International Journal of Medical Engineering and Informatics (IJMEI), Interscience, Concurrency and Computation: Practice and Experience, Progress of Electrical and Electronic Engineering, which Publishing Pt. Ltd.

R. Sitharthan, Centre for Smart Grid Technologies, School of Electrical Engineering, Vellore Institute of Technology, Chennai, India

R. Sitharthan received his B.E. degree in Electrical and Electronics Engineering, M.E. degree in Power Systems Engineering, and Ph.D. degree in Electrical Engineering from the Anna University, India, in 2010, 2012, and 2016, respectively. He is an assistant professor in the School of Electrical Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India. He has completed research funded project as a principal investigator under the ECRA scheme, Science and Engineering Research Board, Department of Science and Technology, Government of India. His research interests include renewable energy systems, artificial intelligence-based control methodology, FACTS devices, IoT applications soft computing techniques, and piezoelectric materials.

Shanmuga Sundar Dhanabalan, Functional Materials and Microsystems Research Group, RMIT University, Melbourne, Victoria 3001, Australia

Shanmuga Sundar Dhanabalan is a researcher at Functional Materials and Microsystems Research Group at RMIT University, Australia. He completed his Ph.D. from Anna University, Chennai, India. He currently leading a team ‘wearable and connected sensors’ at RMIT University, with a focus on materials, flexible and stretchable devices, wearables, optics, and photonics. His studies have led to publications in referred international journals, book chapters, and books in progress as editor. He has presented plenary/keynote, invited talks and guest lectures, oral and poster presentations at scientific meeting at various universities world-wide. Several outcomes have been highlighted by scientific websites (such as Photonics Media, USA). He has served as a reviewer for over 20 prestigious specialist journals. He also served as a topical editor for highly reputed journals including IEEE, Elsevier and Springer journals.

Mahendra Bhatu Gawali, Department of Information Technology, Sanjivani College of Engineering, India

Mahendra Bhatu Gawali received his BE degree in 2008, M.E. degree in 2013 and Ph.D. degree in 2019 from University of Mumbai, MS, India. Currently he working as Professor in IT department of Sanjivani College of Engineering, Kopargaon, Savitribai Phule Pune University, Pune, MS, India. His area of interests is Digital Twin, Cognitive Intelligence, Artificial Intelligence, Cloud Computing, Optimization.

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Published

2023-10-14

How to Cite

Rajesh, M. ., Vengatesan, K. ., Sitharthan, R. ., Dhanabalan, S. S. ., & Gawali, M. B. . (2023). Enhancing Mobile Multimedia Trustworthiness through Federated AI-based Content Authentication: Enhancing Mobile Multimedia. Journal of Mobile Multimedia, 19(06), 1415–1438. https://doi.org/10.13052/jmm1550-4646.1963

Issue

2023: Vol 19 Iss 6

Section

Federated trustworthy artificial intelligence for multimedia data