International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Deepfake Detection Using Artificial Intelligence and Blockchain |
|---|---|
| ABSTRACT | The rapid advancement of artificial intelligence has enabled the generation of highly realistic deepfake videos and images, which pose severe threats to digital trust, privacy, and security. Deepfake media can be misused for political misinformation, identity fraud, cybercrime, and legal evidence manipulation. Existing deepfake detection systems are mostly centralized, making them vulnerable to privacy leakage, model tampering, and lack of trust in detection outcomes. This paper proposes a Blockchain-Enabled Federated CNN–LSTM framework for secure and privacy-preserving deepfake detection. The proposed system uses Convolutional Neural Networks (CNNs) to extract spatial manipulation artifacts from video frames and Long Short-Term Memory (LSTM) networks to capture temporal inconsistencies across frames. Federated Learning allows decentralized training without sharing raw video data, ensuring privacy preservation, while Blockchain technology provides tamper-proof and transparent storage of detection results. Experimental evaluation on benchmark datasets demonstrates that the proposed approach achieves superior accuracy, robustness, privacy, and trustworthiness compared to conventional deepfake detection methods. |
| AUTHOR | BHAVNA PARASTE, DR. SAURABH SHARMA, PROF. SAURABH VERMA Department of Computer Science and Engineering, Baderia Global Institute of Engineering & Management, Jabalpur, Madhya Pradesh, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401038 |
| pdf/38_Deepfake Detection Using Artificial Intelligence and Blockchain.pdf | |
| KEYWORDS | |
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