… An extensive survey on similar technologies like machine … detection, anomaly detection,
Host-based IDS, and Network-… K-Means Clustering machine learning algorithm to analyze the …

… to the rapid development of the Internet of Things (IoT) technology. As a … This paper proposes
an anomaly detection framework for … Different schemes using statistics and deep learning …

… and suggested a non-parametric outlier detection (NPOD) model for … of IoT (exercise intensity
increases-IoT) to solve scientific … is the algorithm function of the person looking through the …

… make an extensive review of … machine learning algorithms that are used to model the
activities, and the complexity of the activities that are being modeled [70][71]. For Anomaly Detection…

… for solving prediction and anomaly detection problems from … and two are for anomaly
detection, have been successfully … Convolutional lstm network: A machine learning approach …

… Machine learning algorithms can improve the accuracy and sensitivity of power grid fault
detection and attack identification. … anomaly detection for wide-area protection using machine …

… traffic characteristics, and detect whether the attack occurs through AdamDNN. … machine
learning and Shannon entropy detection schemes, the detection success rate of this scheme …

… this study aims to develop a deep learning-based identification and prediction method for
machining inspection… using edge detection algorithms and the newly developed approximation …

… Internet of things (IIoT), based on technical principles, the network anomaly detection papers
… forensic framework based on deep learning for Internet of things networks: a particle deep …

… the technology for cyber-attacks and use Machine Learning … the most useful algorithmic tools
in the Machine Learning field … attacker activities in iot through machine learning techniques. …