Malware Detection via Machine Learning and Recognition of Non Stationary Tasks

Alagrash, Yasamin; Badih, Haissam; Rrushi, Julian

doi:10.1109/dasc-picom-cbdcom-cyberscitech49142.2020.00106

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Build the Markov Model1

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Cited by 2 publications

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“…In this work, a Markov models were developed [18]. In a Markov-based dynamical method, the IoT device's emission probability is the likelihood of seeing an RSSI signal given its current state.…”

Section: Build the Markov Modelmentioning

confidence: 99%

Modeling of Human Activity Prediction in Healthcare Internet of Things (Iot) System

Yousif,

Abdullah

2023

acad. sci. j.

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The life of people can be improved simply and conveniently through the use of the Internet of Things (IoT). The healthcare sector is considered to be one of the most encouraging IoT applications. In the current paper, a predicted model of healthcare based on the Internet of Things (IoT) system that uses distinct Markov state-space models is proposed. Here, a real-time Received Signal Strength Indicator link quality assessment technique is followed by a way to identify people's movements and the probability of the next move, Experimental findings The results of the coverage tests internal environments are displayed of the probability of the system patient activity with the change of motion sensor rate of Received Signal Strength Indicator that can detect the human activity for each state in Markov model.

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Section: Build the Markov Modelmentioning

confidence: 99%