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Now showing items 21-26 of 26
Anomaly Detection: A Survey
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
Anomaly detection (AD) is considered one of the important research areas that have a diverse range of application domains. Some of the anomaly detection techniques presented in the literature were specifically implemented ...
Anomaly Detection in Blockchain-Enabled Supply Chain: An Ontological Approach
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
In our work, we propose an anomaly detection framework, for detecting anomalous transactions in business processes from transaction event logs. Such a framework will help enhance the accuracy of anomaly detection in the ...
Scalable Containerized Pipeline for Real-time Big Data Analytics
(
IEEE Computer Society
, 2022 , Conference Paper)
With the widespread usage of IoT, processing data streams in real-time have become very important. The traditional data-stream processing systems are inefficient in processing big data for detecting anomalies, classifications, ...
PCovNet: A presymptomatic COVID-19 detection framework using deep learning model using wearables data
(
Elsevier
, 2022 , Article)
While the advanced diagnostic tools and healthcare management protocols have been struggling to contain the COVID-19 pandemic, the spread of the contagious viral pathogen before the symptom onset acted as the Achilles' ...
Machine Learning Techniques for Network Anomaly Detection: A Survey
(
IEEE
, 2020 , Conference Paper)
Nowadays, distributed data processing in cloud computing has gained increasing attention from many researchers. The intense transfer of data has made the network an attractive and vulnerable target for attackers to exploit ...
Hybrid Machine Learning for Network Anomaly Intrusion Detection
(
IEEE
, 2020 , Conference Paper)
In this paper, a hybrid approach of combing two machine learning algorithms is proposed to detect the different possible attacks by performing effective feature selection and classification. This system uses Random Forest ...