Secure IoT Protocol for Implementing Classified Electroencephalogram (EEG) Signals in the field of Smart Health Care 1 S. Saravanan, 2 M. Lavanya, 3 Chandra Mouli, 4 M. Arunadevi, 5 N. Arulkumar 1 Assistant Professor, Department of Electronics & Communication Engineering, Srinivasa Ramanujan Centre, SASTRA (Deemed to be University), Kumbakonam, 2 Assistant Professor, School of Computing, SASTRA (Deemed to be University), Thanjavur, Tamilnadu 3 Professor & Head, Department of Computer Science, AMC Engineering College, Bengaluru 4 Professor and HOD, Department of MCA, Cambridge Institute of Technology, K.R.Puram, Bangalore 5 Assistant Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore Abstract The present Industrial 4.0 revolution provides massive opportunities in the field of smart manufacturing systems, Artificial Intelligence based systems, Cloud Technology, and Secure data processing. This Industry 4.0 revolution also helps us to address various issues related to secure health care, in terms of the Internet of Things (IoT) environment along with M2M communication. This chapter focuses on the Electroencephalogram (EEG) technique, by observing major changes in human emotional signals. An EEG signal also gives more attention to identify the unusual and misleading signals from elderly patients. This chapter elaborates on the usage of sensors, along with the Internet of Things (IoT) hardware platform, through Message Queue Telemetry Transport (MQTT) communication protocol. This arrangement helps us to find better solutions in detecting and classifying the EEG signals with help of the Support Vector Machine (SVM) algorithm. Classified EEG signals were transferred through the MQTT protocol. It is one of the popular lightweight communication protocols, which are more compatible and simple to integrate with IoT technology. This chapter also highlights the Secure-MQTT protocol between a sensor and cloud in terms of its authentication purposes, by providing a username, strong password, Secure Client identifier, Transport Layer Security (TLS) / Secure Sockets Layer (SSL), and Arduino IoT environment. The overall observation of this chapter will satisfy the audience by knowing the Industrial 4.0 revolution involved in the classification approach of EEG signals, IoT hardware platform, and various security issues related to MQTT communication protocol. Keywords: Industrial 4.0, Electroencephalogram (EEG), Classification of EEG, Internet of Things (IoT), Message Queue Telemetry Transport (MQTT), Secure healthcare