How modern infostealers target macOS systems, leverage Python‑based stealers, and abuse trusted platforms and utilities to ...
A prolific data ransom gang that calls itself Scattered Lapsus ShinyHunters (SLSH) has a distinctive playbook when it seeks ...
How AI and agentic AI are reshaping malware and malicious attacks, driving faster, stealthier, and more targeted ...
Enterprise security faces a watershed as AI tools mature from passive analytics to autonomous operatives in both offense and defense. To date, traditional ...
Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
Abstract: This paper proposes a novel approach to adversarial attacks against machine learning-based network intrusion detection systems (NIDS). Unlike conventional methods that apply feature-space ...
RNN-DAS is an innovative Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, developed for real-time Volcano-seismic Signal Recognition (VSR) using ...
Abstract: Nowadays, the IoT (internet of things) botnet has become a huge threat to network security. In response to this threat, we present a cooperative adaptive network intrusion detection system ...
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