Dr. M.Chithik Raja
@sct.edu.om
Faculty , Information Technology
University of Technology and Applied Sciences Salalah
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Artificial Intelligence, Multidisciplinary, Renewable Energy, Sustainability and the Environment
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Eshrag Refaee, Shabana Parveen, Khan Mohamed Jarina Begum, Fatima Parveen, M. Chithik Raja, Shashi Kant Gupta, and Santhosh Krishnan
Hindawi Limited
The Internet of Things (IoT) has impacted various aspects of life, but its profound effects on the health sector are particularly striking because of its cutting-edge nature. Mobile computing characteristics enable IoT to play a more important role when used with mobile computing. A significant part of the benefits of IoT in healthcare can be attributed to mobile health, which is greatly enhanced by mobile computing. Wearables transmit large amounts of data to IoT devices through sensors, actuators, and transceivers. Threats, attacks, and vulnerabilities abound for data on the Internet of Things. Therefore, addressing IoT-related security, privacy, and vulnerability issues call for a robust security solution. This paper proposes a secure and scalable healthcare data transmission framework in IoT based on an optimized routing protocol. Initially, the health data is collected from various IoT devices like wearable devices and sensors. The raw data is preprocessed via data cleaning and data reduction techniques. K-nearest neighbor (KNN) imputation is performed and principal component analysis (PCA) is employed for dimension reduction of the data. Utilizing modified local binary patterns (MLBP), the features are extracted from the preprocessed data. By combining the fuzzy dynamic trust-based RPL algorithm with the butter ant optimization (BAO) algorithm for low-power and lossy networks, the proposed fuzzy dynamic trust-based RPL (FDT-RPL) protocol improves the overall security of data transmission. The algorithm has been implemented for a smart healthcare system, and the performance is analyzed by comparing it with traditional approaches. The proposed routing protocol provided a secure and scalable healthcare data transmission.
M. Chithik Raja and M. Munir Ahmed Rabbani
IEEE
In the modern world we are using the smart devices for storing data, retrieving data and processing the data on the cloud which is energy users to manage a wide variety of subscribers, reading devices for measuring, billing, disconnection and connection of subscribers from the connection management is an important issue. The performance of these intelligent systems is based on information transfer in the context of storing Big data, so reported data from network should be managed to avoid the malicious activities that including the issues that could affect the quality of service the system. In this paper for control of the reported wireless data and to ensure the veracity of the obtained information, using intrusion detection system is proposed based on the support vector machine and principle component analysis (PCA) to recognize and identify the intrusions and attacks in the smart grid. Here, the operation of intrusion detection systems for different kernel of SVM when using support vector machine (SVM) and PCA simultaneously is studied. To evaluate the algorithm, based on data KDD99, numerical simulation is done on five different kernels for an intrusion detection system using support vector machine with PCA simultaneously. Also comparison analysis is investigated for presented intrusion detection algorithm in terms of time — response, rate of increase network efficiency and increase system error and differences in the use or lack of use PCA. The results indicate that correct detection rate and the rate of attack error detection have best value when PCA is used, and when the core of algorithm is radial type, in SVM algorithm reduces the time for data analysis and enhances performance of intrusion detection.