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Early Detection of Depression: Social Network Analysis and Random Forest Techniques
(J M I R Publications, Inc., 2019-06-10)
[Abstract] Background: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, ...
Annotated Dataset for Anomaly Detection in a Data Center with IoT Sensors
(MDPI AG, 2020-07-04)
[Abstract]
The relative simplicity of IoT networks extends service vulnerabilities and possibilities to different network failures exhibiting system weaknesses. Therefore, having a dataset with a sufficient number of ...
Low Cost Automated Security Audit System
(MDPI, 2021)
[Abstract] In recent years, a quick transition towards digitization has been observed in most organizations. Along with it, certain inherent problems have appeared, such as the increase in cyber threats. Large organizations ...
High Order Profile Expansion to tackle the new user problem on recommender systems
(Public Library of Science, 2019-11-07)
[Abstract]
Collaborative Filtering algorithms provide users with recommendations based on their opinions, that is, on the ratings given by the user for some items. They are the most popular and widely implemented algorithms ...
IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection
(MDPI, 2021)
[Abstract] With advancements in engineering and science, the application of smart systems is increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT restricted power and computing ...
Network Data Flow Clustering based on Unsupervised Learning
(Institute of Electrical and Electronics Engineers Inc., 2019)
[Abstract]: Network communication data analysis is crucial in order to provide an adequate security level in computer infrastructures. As the volume of data and the number of features rise, the difficulties associated with ...
Application of machine learning algorithms for the validation of a new CoAP-IoT anomaly detection dataset
(MDPI, 2023-04)
[Abstract]: With the rise in smart devices, the Internet of Things (IoT) has been established as one of the preferred emerging platforms to fulfil their need for simple interconnections. The use of specific protocols such ...
Measuring Early Detection of Anomalies
(IEEE, 2022)
[Abstract] Early detection is a matter of growing importance in multiple domains as network security, health conditions over social network services or weather forecasts related disasters. It is not enough to make a good ...
Network Anomaly Detection Using Machine Learning Techniques
(MDPI AG, 2020-08-19)
[Abstract]
While traditional network security methods have been proven useful until now, the flexibility of machine learning techniques makes them a solid candidate in the current scene of our networks. In this paper, we ...