Attackers are increasingly using AI to generate adaptable malware that can evade traditional defenses, making familiar security playbooks less reliable by the day.
A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements. The mechanism relies on visual ...
ABSTRACT: The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior using deep learning methods and ensuring interpretability of ...
Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...
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 ...
Although we surveyed only one college, our results align with similar studies, providing an emerging picture of the technology’s use in higher education. Between December 2024 and February 2025, we ...
The Pakistani APT36 cyberspies are using Linux .desktop files to load malware in new attacks against government and defense entities in India. Although the attacks described in the two reports use ...
Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...
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