Results 11 to 20 of about 2,419,123 (314)

Insider Threat Detection Model Using Anomaly-Based Isolation Forest Algorithm

IEEE Access, 2023
Insider attacks may inflict far greater damage to an organization than outsider threats since insiders are authorized users who are acquainted with the business’s system, making detection harder.
Taher Al-Shehari, Muna Al-Razgan, Taha Alfakih, Rakan A. Alsowail, Saravanan Pandiaraj   +4 more
doaj   +2 more sources

Leveraging productivity indicators for anomaly detection in swine breeding herds with unsupervised learning [PDF]

Frontiers in Veterinary Science
IntroductionIn swine disease surveillance, obtaining labeled data for supervised learning models can be challenging because many farms lack standardized diagnostic routines and consistent health monitoring systems.
Mafalda Pedro Mil-Homens, Mafalda Pedro Mil-Homens, Chong Wang, Chong Wang, Giovani Trevisan, Fernanda Dórea, Fernanda Dórea, Daniel C. L. Linhares, Derald Holtkamp, Gustavo S. Silva   +9 more
doaj   +2 more sources

Signature Isolation Forest

International Conference on Artificial Intelligence and Statistics
Functional Isolation Forest (FIF) is a recent state-of-the-art Anomaly Detection (AD) algorithm designed for functional data. It relies on a tree partition procedure where an abnormality score is computed by projecting each curve observation on a drawn ...
Guillaume Staerman, M. Campi, Gareth W. Peters   +2 more
semanticscholar   +3 more sources

Extended Isolation Forest [PDF]

IEEE Transactions on Knowledge and Data Engineering, 2021
12 pages; 21 figures, Published.
Sahand Hariri, Matias Carrasco Kind, Robert J. Brunner   +2 more
openaire   +2 more sources

Optimized Deep Isolation Forest

Pattern Recognition Letters
Lukasz Galka
semanticscholar   +2 more sources

Explainable Anomaly Detection Framework for Maritime Main Engine Sensor Data

Sensors, 2021
In this study, we proposed a data-driven approach to the condition monitoring of the marine engine. Although several unsupervised methods in the maritime industry have existed, the common limitation was the interpretation of the anomaly; they do not ...
Donghyun Kim, Gian Antariksa, Melia Putri Handayani, Sangbong Lee, Jihwan Lee   +4 more
doaj   +1 more source

Effects of forest fragmentation on amazonian understory bird communities [PDF]

Acta Amazonica, 1989
SUMMARYData form an intensive mist-netting mark-recapture program in the central Amazon demostrate significant changes in the undesrtory avian community in isolate patches of 1 and 10 ha of terra firme forest.
Richard O. Bierregaard Jr, Thomas Ε. Lovejoy   +1 more
doaj   +1 more source

A New Extreme Detection Method for Remote Compound Extremes in Southeast China

Frontiers in Earth Science, 2021
The compound heat wave and extreme precipitation events are responsible for severe damages to the environment and human societies. Although major advances have been made in understanding the compound extremes (e.g., drought and heat wave), little is ...
Luqing Wang, Qinglin Zhao, Si Gao, Si Gao, Wei Zhang, Wei Zhang, Li Feng   +6 more
doaj   +1 more source

Efficient Driver Drunk Detection by Sensors: A Manifold Learning-Based Anomaly Detector

IEEE Access, 2022
This study presents an effective data-driven anomaly detection scheme for drunk driving detection. Specifically, the proposed anomaly detection approach amalgamates the desirable features of the t-distributed stochastic neighbor embedding (t-SNE) as a ...
Abdelkader Dairi, Fouzi Harrou, Ying Sun
doaj   +1 more source

Integration of Machine Learning Solutions in the Building Automation System

Energies, 2023
This publication presents a system for integrating machine learning and artificial intelligence solutions with building automation systems. The platform is based on cloud solutions and can integrate with one of the most popular virtual building ...
Bartlomiej Kawa, Piotr Borkowski
doaj   +1 more source