Frontiers

Explainable deep learning approaches and clinical insights for cancer biomarker identification

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

New Phishing Attack Turns n8n Into On-Demand Malware Machine

Hackers are abusing n8n workflows to deliver malware and evade detection, according to Cisco Talos, using trusted automation to bypass security defenses. A trusted automation tool has quietly become a ...
Infosecurity-magazine.com

DeepLoad Malware Combines ClickFix With AI-Generated Code to Avoid Detection

A newly uncovered malware campaign is combining ClickFix delivery with AI generated evasion techniques to steal enterprise user accounts and passwords. The attacks are designed to provide intruders ...
IEEE

Real-Time Detection of Fileless Malware Using Hybrid Deep Learning with CNN and Autoencoder Anomaly Detection

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 ...
Bleeping Computer

New Android malware uses AI to click on hidden browser ads

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 ...
Tom's Guide

Fake Grok app built using generative AI discovered spreading malware on macOS devices

A new macOS malware has been identified by Mosyle, an Apple device management and security firm. The company shared details of the SimpleStealth campaign with 9to5Mac. Simply, the SimpleStealth attack ...
Infosecurity-magazine.com

Malware Manipulates AI Detection in Latest npm Package Breach

A new attempt to influence AI-driven security scanners has been identified in a malicious npm package. The package, eslint-plugin-unicorn-ts-2 version 1.2.1, appeared to be a TypeScript variant of the ...
Scientific Research Publishing

An, J. and Cho, S. (2015) Variational Autoencoder Based Anomaly Detection Using Reconstruction Probability. Special Lecture on IE, 2, 1-18.

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 ...
Scientific Research Publishing

Ferrag, M.A., Maglaras, L., Moschoyiannis, S. and Janicke, H. (2020) Deep Learning for Cyber Security Intrusion Detection: Approaches, Datasets, and Comparative Study. Journal ...

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 ...
Futurism

Malware Is Now Using AI to Rewrite Its Own Code to Avoid Detection

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