The approach models inter-device state correlations using a heterogeneous graph structure and partitions behavior patterns through iterative community detection and automated semantic annotation, and represents normal behavior by embedding and clustering of state sequences.
A machine learning-based framework to tackle issues in traditional systems in traditional systems is introduced by combining large language models (LLMs) and is effective in identifying possible threats as well as filling the semantic gap.
Mamoon M. Saeed, Rashid A. Saeed, Salah Hagahmoodi et al.· Baghdad Science Journal· 0 citations
Traditional Internet of Things (IoT) security solutions often rely on heavy cloud-based or gateway-class infrastructure, which is frequently unsuitable for resource-limited hardware due to latency, power, and memory constraints. This paper proposed a resource-aware behavioral Intrusion Detection System (IDS) designed f...
Sofyan Bisher, Anas Fawaza, Tarek Mawed et al.· International Conference on...· 0 citations
This study proposes a hybrid machine learning-based intrusion detection and prevention framework for securing IoT networks that integrates Isolation Forest, Autoencoder, Extreme Gradient Boosting, and Bidirectional Long Short-Term Memory models within a stacked ensemble architecture to improve attack detection while re...
Ruthwik Palem, Likhith Reddy Peketi, Vanathi M et al.· Cureus Journal of Computer S...· 0 citations
As MNI becomes increasingly vulnerable to new kinds of attacks from the cyber world, accurate and timely detection of intrusions becomes a primary key to the power of cybersecurity. More complex attack patterns, complex traffic interactions within large scales are not very collaborable with the typical signature-based...
S. Nagendrudu, Shaik Mohammed Anays, F. Mahammad et al.· 2026 International Conferenc...· 0 citations
A hybrid IDS framework that integrates supervised Random Forest classification, unsupervised Isolation Forest anomaly monitoring, and Kolmogorov–Smirnov (KS)-based concept drift monitoring is presented, providing initial evidence of generalization to one held-out attack family but should not be interpreted as proof of...
Muath A. Obaidat, Meryem Abouali, Aneeza Shakeel· Italian National Conference...· 0 citations
A two-tier hybrid IDS that uses a Random Forest model for quick initial detection and a Neural Network for deeper analysis of suspicious traffic is proposed that provides a balanced and efficient solution that overcomes key limitations of existing IDS models and offers a pathway towards a more robust real-time IoT intr...
Research Paper, Wong Zoey, Yu Watanabe et al.· International Journal of Eme...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
