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The Hacker News3d
Why top SOC teams are shifting to Network Detection and Response
NDR solutions uncover hidden threats missed by legacy tools by analyzing encrypted traffic, lateral movement, and blind spots ...
GitHub14d
Network Analysis Made Simple
Welcome to the GitHub repository for Network Analysis Made Simple! This is a tutorial designed to teach you the basic and practical aspects of graph theory. It has been presented at multiple ...
IEEE29d
GTAE-IDS: Graph Transformer-Based Autoencoder Framework for Real-Time Network Intrusion Detection
Abstract: Network intrusion detection systems (NIDS) utilize signature and anomaly-based methods to detect malicious activities within networks. Advances in machine learning (ML) and deep learning (DL ...
IEEE1mon
Protocol-Agnostic and Packet-Based Intrusion Detection Using a Multi-Layer Deep-Learning Architecture at the Network Edge
Abstract: Intrusion Detection (ID) faces multiple challenges ... This paper presents a novel approach to ID in network traffic within edge computing environments using a Neural Network (NN) model. The ...
Frontiers1y
Ensemble machine learning-based recommendation system for effective prediction of suitable agricultural crop cultivation
Machine learning (ML) offers the most effective tool to predict ... and result processing) are accomplished using the Python programming language. We preprocess the collected raw data to make them ...