How modern infostealers target macOS systems, leverage Python‑based stealers, and abuse trusted platforms and utilities to ...
Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
A machine learning-based methodology to uniquely identify network devices using DNS query patterns, combining unsupervised clustering (K-Means) with supervised classification (Random Forest).
Abstract: Task scheduling in distributed cloud and fog computing applications must be efficient to optimize resource utilization, minimize latency, and comply with strict service level agreements. The ...
Multi-document abstractive summarization on the NewsSumm dataset (Indian English news). We explore whether document ordering matters for BART-based summarization by weighting articles based on ...
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