The Defensive Techniques Security Teams Need For AI-Driven Malware

Attackers are increasingly using AI to generate adaptable malware that can evade traditional defenses, making familiar security playbooks less reliable by the day.
SecurityWeek

Cyber Insights 2026: Malware and Cyberattacks in the Age of AI

How AI and agentic AI are reshaping malware and malicious attacks, driving faster, stealthier, and more targeted ...
Bleeping Computer

New SantaStealer malware steals data from browsers, crypto wallets

A new malware-as-a-service (MaaS) information stealer named SantaStealer is being advertised on Telegram and hacker forums as operating in memory to avoid file-based detection. According to security ...
Bleeping Computer

Google exposes BadAudio malware used in APT24 espionage campaigns

China-linked APT24 hackers have been using a previously undocumented malware called BadAudio in a three-year espionage campaign that recently switched to more sophisticated attack methods. Since 2022, ...
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

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...
IEEE

Anomaly Detection in IoT Networks: A Deep Learning Approach Using Autoencoders

Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...
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 ...
Dark Reading

Russia's APT28 Targets Microsoft Outlook With 'NotDoor' Malware

APT28, the state-sponsored threat group tied to Russian intelligence, is weaponizing Microsoft Outlook through a new backdoor researchers call "NotDoor." The backdoor malware was first identified by ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
Frontiers

Thyroid nodule segmentation in ultrasound images using transformer models with masked autoencoder pre-training

Introduction: Thyroid nodule segmentation in ultrasound (US) images is a valuable yet challenging task, playing a critical role in diagnosing thyroid cancer. The difficulty arises from factors such as ...