News

Silent Infiltrators: Trusted RMM Tools Become Hidden Attack Vectors

Ransomware groups are exploiting trusted RMM tools to bypass detection, persist and exfiltrate data. Defenders have to move ...
Decrypt1d

Researchers Uncover Undetectable Malware Draining Crypto Browser Wallets

Security firm Mosyle has disclosed ModStealer, a cross-platform malware that evades antivirus software and targets browser ...
IEEE17d

Depression Detection Through EEG Signal Analysis: A Convolutional Autoencoder Deep Learning Model

Abstract: Depression is a debilitating and enervating mental health disorder that requires attention for necessitating accurate and efficient diagnostic techniques ...
C&EN25d

Reducing Spectral Confusion in Microplastic Analysis: A U-Net Deep Learning Approach

Department of Chemistry and Chemical Engineering, Inha University, Incheon 22212, Republic of Korea Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Republic of Korea ...
The Hacker News26d

Noodlophile Malware Campaign Expands Global Reach with Copyright Phishing Lures

The threat actors behind the Noodlophile malware are leveraging spear-phishing emails and updated delivery mechanisms to deploy the information stealer in attacks aimed at enterprises located in the U ...
IEEE27d

Autoencoder-Based Approaches for Upper Limb Use Detection

Abstract: Feature extraction is an essential step in traditional machine learning approaches for detecting upper limb use employing movement data from inertial measurement units. However, manual ...
Scientific Research Publishing27d

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 ...