Emergent deep learning for anomaly detection in internet of everything

Y Djenouri, D Djenouri, A Belhadi… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
This research presents a new generic deep learning (DL) framework for anomaly detection
in the Internet of Everything (IoE). It combines decomposition methods, deep neural …

NODSTAC: novel outlier detection technique based on spatial, temporal and attribute correlations on IoT Bigdata

MV Brahmam, S Gopikrishnan - The Computer Journal, 2024 - academic.oup.com
An outlier in the Internet of Things is an immediate change in data induced by a significant
difference in the atmosphere (Event) or sensor malfunction (Error). Outliers in the data cause …

基于数据标签的智能电网监控与异常检测.

管荑, 谢小川, 胡琳, 尚鹏… - … /Gongcheng Kexue Yu …, 2023 - search.ebscohost.com
智能电网是电网的智能化系统, 是以输电网, 各级电网协调发展为基础的通信信息支撑平台,
是包括输变电, 配电与电力调度的各电压等级的信息化, 自动化和互动化等为特征的高度一体化 …

A Perceptually Important Points Approach Based on Imputation Clustering with Weighted Distance Techniques for Big Data Reduction in Internet of Things Cloud

EA Edje, ALM Shaffie, CW Howe - Neural Processing Letters, 2023 - Springer
IoT sensing devices tend to generate large volume of data samples consisting of relevant
and irrelevant sensed data records. Irrelevant data points are regarded as data redundancy …

A review of data analytic algorithms for outlier detection on the internet of things ecosystem

OJ Iwomi, EE Abel, G Omede, E Atonuje, C Ogeh… - Science World …, 2024 - ajol.info
In the last few years, outlier detection has drawn a lot of attention. New technologies,
including the Internet of Things (IoT), are recognized as one of the most important sources of …

[PDF][PDF] Anomaly-based Intrusion Detection Techniques in Internet of Things Ecosystem: A Review

EA EDJE - FUPRE Journal of Scientific and Industrial Research, 2024 - journal.fupre.edu.ng
The term" internet of things"(IoT) describes a new paradigm for communication in which
devices are equipped with sensors and actuators to detect their environment, connect with …