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AWS intruder achieved admin access in under 10 minutes thanks to AI assist, researchers say

LLMs automated most phases of the attack A digital intruder broke into an AWS cloud environment and in just under 10 minutes ...
Cyber Defense Magazine

The AI Arms Race Is Here: How Enterprises Must Weaponize Data and Autonomous Defense to Survive the Next Generation of Cyberattacks

Enterprise security faces a watershed as AI tools mature from passive analytics to autonomous operatives in both offense and defense. To date, traditional ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

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 ...
IEEE

Implementing Practical Problem-Space Adversarial Attacks on Modern Network Intrusion Detection Systems

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 ...
GitHub

RNN-DAS: A New Deep Learning Approach for Detection and Real-Time Monitoring of Volcano-Tectonic Events Using Distributed Acoustic Sensing

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 ...
IEEE

CAD-IDS: A Cooperative Adaptive Distributed Intrusion Detection System with Fog Computing

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 ...