The surge in digital transactions has paved the way for an alarming rise in credit card fraud, compelling the need for robust detection systems. The swift progress of technology has transformed customer payment habits...
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The Computational Visual Media(CVM)conference series is intended to provide a prominent international forum for exchanging innovative research ideas and significant computational methodologies that either underpin or ...
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The Computational Visual Media(CVM)conference series is intended to provide a prominent international forum for exchanging innovative research ideas and significant computational methodologies that either underpin or apply visual media.
Malware, as a pervasive cyber threat, jeopardizes both digital infrastructure security and the broader societal functioning and safety. This paper investigates the resilience of the LeNet convolutional neural network ...
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The recommendation systems are used in different sectors to offer tailored services for users. The major applications of these systems are in the entertainment sector, where the movie-based recommendation systems can ...
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Automatic feature extraction from medical images is one of the most important aspects of early disease detection and treatment. This work presents a novel method for autonomously extracting features from diabetic reti...
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Cloud technology has the power to manage computational efficiency. Cloud provides easy access but is also vulnerable to security measures as the internet is open to everyone. Adding cryptography and steganography to t...
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This study addresses the challenge of automatically interpreting and classifying baby cries to discern various needs such as hunger, burping, tiredness, discomfort, or belly pain. Existing research lacks precise diffe...
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Smoking and excessive alcohol consumption remain pressing public health issues. This research aimed to develop Machine Learning (ML) models leveraging sensor and biomarker data to predict smoking and drinking behavior...
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Ethernet and wireless-based technologies play an important role in the Internet of Medical Things. The new healthcare scenarios require a deterministic communication system with real-time capabilities. In remote surge...
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The Internet of Medical Things (IoMT) has transformed the healthcare sector by allowing for the continuous gathering, transfer, and analysis of medical data via networked ***, as IoMT has become more integrated into h...
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The Internet of Medical Things (IoMT) has transformed the healthcare sector by allowing for the continuous gathering, transfer, and analysis of medical data via networked ***, as IoMT has become more integrated into healthcare systems, it has been vulnerable to cybersecurity attacks, posing dangers to patient safety and data privacy. This study tackles the essential challenge of safeguarding the IoMT ecosystem by implementing cutting-edge deep learning approaches for threat identification and *** study begins by looking at a variety of cyber risks that the IoMT faces, including as backdoors, DDoS assaults, MITM assaults, ransomware and SQL *** hostile operations may impair medical services and jeopardize critical med- ical *** combat these risks, we offer a strong intrusion detection system, that constantly monitors the IoMT architecture for any unusual *** findings of this research contribute significantly to the development of a secure and resilient medical IoT *** performance metrics of the proposed intrusion detection system, including accuracy, precision, recall, and F1 Score, were evaluated for four different models: CNN, Autoencoder, Transformer Network, and LSTM *** LSTM Network ex- hibited exceptional performance, achieving an accuracy of 97%, precision of 93%, recall of 96%, and an F1 Score of 94%.The compiled model, named Adam-LSTM, leverages the strengths of the Adam optimizer and LSTM architecture. Comparative anal- ysis with alternative algorithms demonstrated the superiority of the proposed approach in accurately and efficiently identifying *** IoMT can supply dependable healthcare services to patients while preserving their sensitive medical information by proactively securing digital health through deep learning-based threat *** study provides the groundwork for future breakthroughs in medical IoT cybersecurity solutions and promotes the idea of a smarter and saf
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