DataBreachToday

Chinese Cybercrime Group Deploys AI-Coded Malware Campaigns

Proofpoint says Chinese cybercrime group TA4922 is using AI-assisted phishing and apparently LLM-developed malware, including ...

AI-built ransomware toolkit automates EDR evasion, AD discovery

A threat actor is using an AI-built ransomware attack toolkit that automates Active Directory discovery and helps evade ...
The Hacker News

Endpoint Detection & Response Is Now Table Stakes — Here's What Comes Next

New Bitdefender research reveals that 97.7% of respondents now use endpoint detection and response (EDR). That number might seem high compared to commonly accepted market penetration estimates, ...
IEEE

Zero-Day Malware Detection Using Autoencoder and Hybrid Deep Learning Model

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 ...
AlphaGalileo

Unmasking Hidden Threats: Adaptive Encrypted Malware Detection via FC-MAE

Sub-headline: BIT researchers introduce Malcom to tackle cross-domain encrypted traffic detection using self-supervised learning. A significant technical pain point in cybersecurity is the heavy ...
TechRepublic

Microsoft: Hackers Are Using WhatsApp to Deliver Malware to Windows PCs

Hackers are using WhatsApp messages to deliver malware to Windows PCs, exploiting user trust and attachments to trigger stealthy, multi-stage attacks. A new wave of attacks is turning trusted WhatsApp ...
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 ...
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 ...