Are Your AI Assistants Under Attack?

Many users utilize an AI assistant to handle their inbox, leaving them vulnerable to attack. AI agents are becoming ...
Dark Reading

How Malware Authors Are Incorporating LLMs to Evade Detection

Threat actors are testing malware that incorporates large language models (LLMs) to create malware that can evade detection by security tools. In an analysis published earlier this month, Google's ...
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 ...
Morningstar

Best AI-Powered Security Software (2025): McAfee Named Top Protection Against Deepfakes, Scams, and Malware by Software Experts

McAfee - a global leader in online protection for consumers, offering adaptive solutions that safeguard personal data, privacy, and identity in an always-connected world. The announcement comes at a ...
Bleeping Computer

Microsoft: SesameOp malware abuses OpenAI Assistants API in attacks

Microsoft security researchers have discovered a new backdoor malware that uses the OpenAI Assistants API as a covert command-and-control channel. The company's Detection and Response Team (DART) ...
Scientific Research Publishing

Al-Qatf, M., Lasheng, Y., Al-Habib, M. and Al-Sabahi, K. (2018) Deep Learning Approach Combining Sparse Autoencoder with SVM for Network Intrusion Detection. IEEE Access, 6 ...

ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...
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 ...
Mobile ID News

Study Reveals 2,400+ Mobile Authentication Malware Variants, Highlighting Growing Security Threats

A comprehensive study by mobile security firm Zimperium has identified more than 2,400 distinct malware variants specifically designed to target mobile authentication systems and multi-factor ...
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 ...