Phishing attacks have emerged as a significant cybersecurity threat to e-commerce platforms, targeting users to obtain sensitive information such as login credentials, banking details, and financial records. Existing machine learning and deep learning approaches often suffer from limitations related to redundant featur...
B. B. Gupta, Akshat Gaurav, Shin-Hung Pan et al.· International Journal of Dat...· 0 citations
Deep learning detectors for online misinformation report near-perfect in-domain accuracy, yet deployment faces distribution shift. This study asks whether such scores reflect a transferable ability to separate true from false content, auditing across three public corpora needing no social-media interface: LIAR statemen...
R. Raman, S. Salman, Babasaheb Jadhav et al.· International Journal on Sem...· 0 citations
The global Internet of Things (IoT) network has experienced unprecedented expansion, reaching 75.44 billion connected devices worldwide. Due to this rapid growth, the IoT ecosystem has become larger but also more vulnerable to various threats in cyberspace. As a result, this situation has accelerated the development of...
Mosiur Rahaman, Nicko Cajes, V. Arya et al.· Journal of Web Engineering· 0 citations
ATTEND, a multi-task neural network for substance classification and detection of 18 overdose symptoms, with symptom normalization to standardized MedDRA concepts, which is scalable, privacy-preserving, and suitable for real-time monitoring of drug abuse signals is proposed.
Sudhakar Kumar, S. Singh, Satvik Pathak et al.· International Journal of Int...· 0 citations
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