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Ram Chandra Barik on Muck Rack

Ram Chandra Barik

As seen in: Nature, Blockchain in Healthcare Today
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Articles

Enhancing anomaly-based zero-day attack detection framework using CNN-driven feature extraction and OC-SVM

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By Sudhanshu Sekhar Tripathy, Bichitrananda Behera, D. Samuel Kollie Jr., Ram Chandra Barik, Rahul Priyadarshi, Rakesh Ranjan
| Nature Verified
Abstract Zero-day attacks exploit previously unknown vulnerabilities, posing a significant challenge for traditional Intrusion Detection Systems (IDS) that depend on known attack signatures. Detecting such threats requires models capable of identifying anomalous patterns in network traffic without prior knowledge.
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Stacked multi-fusion CNN: an adaptive attention model for privacy preserving deepfake forensics

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By Minati Mishra, Ram Chandra Barik, Devendra Kumar Yadav, Dilip Prasad, Arif Ahmed Sekh, Jayanti Rout
| Nature Verified
Abstract The emergence of Generative Artificial Intelligence (Gen-AI) and Generative Adversarial Network (GAN)-based deepfakes poses significant security risks in sociocultural and sociopolitical domains. This necessitates the development of advanced and effective detection methods to prevent vulnerability in social networks. Classical Machine Learning (ML) algorithms have their limitations, especially in classifying the deepfakes.
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Hyperledger Fabric-Powered Digital Identity Scheme: Transforming CIA-Triad Security in IoMT Integrated Healthcare Eco-System

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By Sanjay Jena, Ram Chandra Barik, Saroj Padhan
| Blockchain in Healthcare Today Verified
DOI: https://doi.org/10.30953/bhty.v8.411 Keywords: Biomedical, blockchain, confidentiality, healthcare, integrity Download data is not yet available. References Goldberg R, Pitts PJ, Hinkel J. Healthcare Futures: Opportunities, Challenges and Risks in a Blockchain-Driven Environment. Blockchain in Healthcare Today.
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