[HTML][HTML] Advanced R-GAN: Generating anomaly data for improved detection in imbalanced datasets using regularized generative adversarial networks
The high prevalence of fraud in contemporary financial transactions necessitates advanced
anomaly detection systems to address the significant imbalance between legitimate and …
anomaly detection systems to address the significant imbalance between legitimate and …
Deep optimal isolation forest with genetic algorithm for anomaly detection
Anomaly detection is one of the crucial research topics in artificial intelligence,
encompassing various fields such as health monitoring, network intrusion detection, and …
encompassing various fields such as health monitoring, network intrusion detection, and …
Anomaly Detection Based on Isolation Mechanisms: A Survey
Anomaly detection is a longstanding and active research area that has many applications in
domains such as finance, security, and manufacturing. However, the efficiency and …
domains such as finance, security, and manufacturing. However, the efficiency and …
An optimized isolation forest based intrusion detection system for heterogeneous and streaming data in the industrial Internet of Things (IIoT) networks
SA Elsaid, A Binbusayyis - Discover Applied Sciences, 2024 - Springer
Abstract While conventional Intrusion Detection Systems (IDS) are essential for defending
against intruders in the Industrial Internet of Things (IIoT), handling data from heterogeneous …
against intruders in the Industrial Internet of Things (IIoT), handling data from heterogeneous …
Federated Learning-Based Anomaly Detection with Isolation Forest in the IoT-Edge Continuum
Traditional methods for ensuring security and privacy face challenges in safeguarding
multimedia data within the IoT-edge continuum, as their significant computational demands …
multimedia data within the IoT-edge continuum, as their significant computational demands …
[HTML][HTML] SemanticMask: a contrastive view design for anomaly detection in tabular data
Contrastive learning based on data augmentation techniques has recently achieved
substantial advancement in learning a representation well-suited for anomaly detection in …
substantial advancement in learning a representation well-suited for anomaly detection in …
Anomaly detection in streaming data using isolation forest
MS Kareem, LAN Muhammed - 2024 Seventh International …, 2024 - ieeexplore.ieee.org
In the era of constant data generation and exchange, the concept of data streams, which
entails the rapid and organized transmission of vast volumes of data online, has become …
entails the rapid and organized transmission of vast volumes of data online, has become …
AttRel: Single Module Based Joint Entity and Relation Extraction with Attention Enhanced Text Embedding
Abstract Information extraction is a vital subtask of knowledge graph constructions, where
the joint extraction of entities and relations in the form of triples is an essential component …
the joint extraction of entities and relations in the form of triples is an essential component …
An AUTOSAR-Based Framework for Multi-Core Communication System
J Wei, J Gao, W Ma, W Zhao… - 2024 2nd International …, 2024 - ieeexplore.ieee.org
As automotive electronic and electrical architectures evolve from distributed systems toward
domain integration and service-oriented centralized designs, the functional demands of …
domain integration and service-oriented centralized designs, the functional demands of …
An Empirical Characterization of the Stability of Isolation Forest Results
Abstract Isolation Forests (IForest), a specific variant of Random Forests tailored for anomaly
detection, operate by isolating points through recursive partitioning. Despite their …
detection, operate by isolating points through recursive partitioning. Despite their …