Microsoft

When prompts become shells: RCE vulnerabilities in AI agent frameworks

New research exposes how prompt injection in AI agent frameworks can lead to remote code execution. Learn how these ...
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.
IEEE

Hybrid Deep Learning Pipeline with BiLSTM-Attention Autoencoder for Malware Detection

Abstract: This paper presents a Deep Neural Network-based approach for detecting malware. Malware detection is one of the major problems that has increasing challenges due to the sheer volume of new ...
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 ...
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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