ESET uncovers AI-powered PromptLock ransomware using OpenAI gpt-oss:20b model, complicating detection with variable Lua ...

Studies have proposed plant disease detection models based on optimized CNNs [17]- [20]. A hybrid deep learning model combining CNN and optimized recurrent neural network was developed for precise ...

A cybersecurity platform, under development for eight years at Sandia National Laboratories to detect and analyze advanced malware threats, is now publicly available, giving defenders in the public ...

Microsoft unveils Project Ire, an autonomous AI system that reverse-engineers software to detect and block malware without human input.

Methods A multimodal deep-learning model with transformers was developed for real-time recurrence prediction using baseline clinical, pathological, and molecular data with longitudinal laboratory and ...

Traditional intrusion detection systems (IDS) often face difficulties in identifying these new and evolving threats since they rely on pre-established attack patterns or signatures. This study aims to ...

Android OS is an enticing target for attacks due to its popularity. Malware attacks are prevalent and growing. Further, the attack pattern is changing rapidly to avoid intrusion detection. Thus, ...

Methods: This study proposes a novel approach for ASD detection utilizing deep learning and advanced feature selection techniques. A hybrid model combining Stacked Sparse Denoising Autoencoder (SSDAE) ...

The Bumblebee malware SEO poisoning campaign uncovered earlier this week aimpersonating RVTools is using more typosquatting domainsi mimicking other popular open-source projects to infect devices ...

Cybercriminals are using TikTok videos to trick users into infecting themselves with Vidar and StealC information-stealing malware in ClickFix attacks.