Abstract: Malware continues to pose a serious threat to cybersecurity, especially with the rise of unknown or zero day attacks that bypass the traditional antivirus tools. This study proposes a hybrid ...

Cybersecurity has always been the focus of Internet research. Malware refers to software intentionally designed to harm computer systems, networks, or users by stealing, corrupting data, disrupting ...

Sub-headline: BIT researchers introduce Malcom to tackle cross-domain encrypted traffic detection using self-supervised learning. A significant technical pain point in cybersecurity is the heavy ...

Biomarkers play a pivotal role in contemporary cancer immunotherapy by guiding diagnosis, patient stratification, therapeutic decision-making, and longitudinal assessment of treatment responses.

Abstract: Fileless malware represents a rising and complex challenge in cybersecurity, primarily due to its capability to avoid conventional detection strategies by operating entirely within a ...

Android malware using artificial intelligence has been discovered carrying out hidden ad fraud on infected devices. It automatically clicks ads through concealed browser windows and spreads mainly ...

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In 2023, Ethan Mollick and Lilach Mollick published a paper titled Assigning AI: Seven Approaches for Students, with Prompts. At the time, generative AI tools were far less capable than what we now ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...