Dr. M.Chithik Raja

@utas.edu.om

Faculty , Information Technology
University of Technology and Applied Sciences Salalah

Dr. M.Chithik Raja


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https://researchid.co/chithik43
Dr. Chithik Raja Mohamed Sinnaiya is a Lecturer at IT-Dept. CCIS,UTAS-SLL in Oman. He has a diverse academic background, holding a Ph.D. from AMET University, an M.E. from Anna University, an M.Sc. from M.K. University, and a B.Sc. from M.K. University. His professional experience spans several institutions, including Mekelle University in Ethiopia, Surya College of Engineering and Technology, Vickram College of Engineering, GTN Arts College, and Mary Matha Arts & Science College.

Dr. Chithik’s research interests lie in computer science and cybernetics. He has published 28 journal articles, 5 books, and 2 conference proceedings. His work has garnered 26 citations and an h-index of 3. He has also been recognized with awards such as the Most Outstanding Educator and Researcher by the International Organization of Educators and Researchers in 2024 and the Best Student Mentor by the University of Technology and Applied Sciences Salalah in 2023.

In addition to his academic and res

EDUCATION

Ph.D. in the Faculty of Engineering and Technology from AMET University in January 2022, with a dissertation titled “Studies On Hybrid Machine Learning Algorithms For Intruder
M.E. from Anna University, an M.Sc. from Wakf Board College, under Madurai Kamaraj University and a B.Sc. from H.K.R.H. College, also affiliated with Madurai Kamaraj University,
Higher Secondary Certificate (HSC) in Bio-Maths from V.M.G.H.S. School,
Secondary School Leaving Certificate (SSLC) from the V.M.G.H.S. school,

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Multidisciplinary, Renewable Energy, Sustainability and the Environment
12

Scopus Publications

287

Scholar Citations

8

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • Analysing Cyber Attacks on Personal Data and Mitigation Using AI-Driven Techniques
    Venkateswaran Radhakrishnan, Suresh Palarimath, Mohamed Ashik, Mohammed Al Mahri, Chithik Raja Mohamed, S Baghavathi Priya
    Proceedings of 2nd International Conference on Multi Agent Systems for Collaborative Intelligence Icmsci 2026, 2026
    The frequency and complexity of cyber attacks directed at individuals have increased alarmingly with dire consequences to sensitive personal information, financial resources, and online personas. As attackers refine their tactics, leaving them unstable, conventional ameliorative measures tend to be ineffective in managing such risks. Artificial Intelligence (AI) and Machine Learning (ML) are proving to be crucial in improving cybersecurity allowing for proactive and extremely dynamic measures that help monitor and thwart malicious acts at any time. This paper reveals the nature of cyber attacks on individuals and discusses major types of attacks such as phishing, identity theft, ransomware, and social engineering. It also describes in detail the AI and ML techniques aimed at combating these types of attacks such as supervised learning, unsupervised learning, deep learning, and natural language processing. This survey assesses the implications of the relative strength, weaknesses and effectiveness of the approaches on individuals in the context of the prospects of future cyber security tools.
  • Behavioral Anomaly Detection in Big Data Streams: An Attention-Enhanced LSTM Approach for Privacy-Aware Zero-Day Attack Detection
    M. Chithik Raja, Mohammed Musallam Bakhit Al Mahri
    Proceedings of the 7th International Conference on Innovative Data Communication Technologies and Application Icidca 2025, 2025
    Zero-day attacks become a serious threat for today’s Big Data Stream, which their behaviors are unknown and there exists not predefined signatures about them. Such new attacks are not detected by the classical signature-based intrusion detection systems (IDS). A Deep Learning Based Method for Zero-Day Attack Detection through the Behaviour Analysis inBig Data Stream. This article presents a system-level framework that adopts deep learning technique using for the detection of zero-day attack. We use the recently published CIC-IDS2023 data set which offers realistic zero-day attack simulations and a wide range of system telemetry. Our approach utilizes a Long Short-Term Memory (LSTM) network combined with attention mechanisms to model temporal behavior patterns from process, network, and file system activities. Experimental results demonstrate that the proposed model achieves 98.7% accuracy, 97.4% precision, 96.9% recall, and an F1-score of 97.1% in detecting zero-day attacks, outperforming existing machine learning and deep learning baselines. The study also includes ablation studies and feature importance analysis, confirming the efficacy of behavioral features and temporal modeling. This work contributes to advancing proactive cybersecurity through AI-driven behavioral anomaly detection.
  • AI-Driven Helmet Detection in Construction Zones: A YOLOv8X Approach for Sustainable Safety Monitoring
    M. Chithik Raja, Mohamed Musallam Al-Mahr, Wasim Haidar, Suresh Palarimath
    2nd Asian Conference on Intelligent Technologies Acoit 2025, 2025
    The enforcement of personal protective equipment (PPE) compliance, particularly helmet usage, is a critical determinant of occupational safety in high-risk environments such as construction sites. This paper presents a robust, deep learning-driven framework for real-time helmet detection leveraging the YOLOv8X architecture—an advanced variant of the You Only Look Once (YOLO) family. The proposed system autonomously identifies workers and classifies their helmet-wearing status by detecting "head" and "helmet" instances using high-resolution industrial imagery. A curated dataset of 5,000 annotated images, enriched with diverse construction, manufacturing, and mining scenarios, was employed for training and evaluation. The YOLOv8X model achieves a mean Average Precision of 93.3%, with helmet AP of 93.2% and head AP of 93.55%, outperforming YOLOv3-v6, SSD, and Faster R-CNN. With an inference speed of 37.2 FPS and training efficiency of 2.045 hours, the model demonstrates a superior accuracy-latency trade-off suitable for edge deployment. A SHAP-based interpretability analysis confirms the model’s reliance on semantically meaningful features. Furthermore, we propose a privacy-preserving inference pipeline with on-device processing and facial anonymization. This work contributes a scalable, real-time safety monitoring solution aligned with smart city and Sustainable Development Goal (SDG) offering a transformative approach to proactive risk mitigation in industrial environments.
  • Measuring Marketing Effectiveness and Return on Investment
    Nelapatla Swetha, Ponthala Harshavardhan, Tolem Kusuma, M. Chithik Raja
    Predictive Analytics and Generative AI for Data Driven Marketing Strategies, 2024
    For businesses looking to maximize resource allocation and improve performance, accurate measurement of marketing efforts and Return on Investment is crucial. This study thoroughly examines a variety of tactics, indicators, and industry best practices that are essential for assessing marketing efficacy and Return on Investment. Businesses use a variety of methods to evaluate the results of their marketing initiatives because they understand how important measurement is. Organizations use a variety of tactics to obtain comprehensive insights, ranging from conventional techniques like market share analysis and customer surveys to cutting-edge digital analytics tools. To help businesses measure aspects like lead generation, conversion rates, customer acquisition costs, and customer lifetime value, Key Performance Indicators are crucial to this assessment process. Measuring marketing effectiveness is not without its difficulties, though. Difficulties include handling data privacy concerns, attribution models, and accurately tying marketing efforts to results. To tackle these obstacles, a sophisticated strategy is needed, utilizing technology and techniques that correspond with changing consumer preferences and market conditions. The study also looks at recent developments in marketing analytics. Predictive analytics is becoming more and more popular as machine learning and artificial intelligence progress, giving businesses the ability to predict marketing results more precisely. Additionally, becoming essential to contemporary measurement techniques are real-time analytics and an emphasis on customer experience metrics.
  • Breast Cancer Diagnosis from Ultrasonic Image and Histopathology Image Using Deep Learning Approach
    Chithik Raja Mohamed, Mohammad Musallam Al-Mahri, Mohamed Mallick, Arwa Said Salim Al-Shanfari
    Communications in Computer and Information Science, 2024
  • Virtual and Augmented Reality in Interactive Entertainment: Unlocking New Dimensions of Immersive Interaction
    Jasim Sharki Ghulam Al Balushi, Malak Ibrahim Ahmed Al Jabri, Suresh Palarimath, Chithik Raja Mohamed, Venkateswaran Radhakrishnan, Muni Balaji Thumu
    2024 2nd International Conference on Computing and Data Analytics Iccda 2024 Proceedings, 2024
    Virtual Reality (VR) offers an immersive experience with position tracking and 3D near-eye displays, enabling users to enter virtual surroundings. Conversely, Augmented Reality (AR) superimposes computer-generated content onto the real world, integrating digital and physical environments through visual, aural, tactile, and other sensory modalities. Both technologies are transforming user engagement with content, providing the opportunity to explore remote locations, communicate with digital characters, or assume leading roles in interactive entertainment events. While VR completely immerses users in simulated surroundings, AR enriches real-world contexts by incorporating interactive elements and contextual data. This study examines the transformative effects of VR and AR in interactive entertainment, emphasizing its various uses, benefits, and constraints. It emphasizes how new technologies have transformed narrative, facilitating enhanced user involvement and a more dynamic feeling of presence. The review analyzes the present and prospective capabilities of VR and AR in transforming social interactions, narrative-centric experiences, and cooperative gameplay. In addition to entertainment, the article examines the ramifications of AR and VR in education, training, and healthcare, where immersive environments demonstrate significant efficacy. The report highlights the crucial impact these technologies have in enhancing human-computer interaction across various industries.
  • Predict network intruder using machine learning model and classification
    Artificial Intelligence and Knowledge Processing Methods and Applications, 2023
  • Secure and Scalable Healthcare Data Transmission in IoT Based on Optimized Routing Protocols for Mobile Computing Applications
    Eshrag Refaee, Shabana Parveen, Khan Mohamed Jarina Begum, Fatima Parveen, M. Chithik Raja, Shashi Kant Gupta, Santhosh Krishnan
    Wireless Communications and Mobile Computing, 2022
    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.
  • Comparison of hybrid machine learning algorithms for intruder detection
    International Journal of Psychosocial Rehabilitation, 2020
  • Analytical inspection of centrality measures in social networking
    Journal of Advanced Research in Dynamical and Control Systems, 2018
  • Combined analysis of support vector machine and principle component analysis for IDS
    M. Chithik Raja, M. Munir Ahmed Rabbani
    Proceedings of the International Conference on Communication and Electronics Systems Icces 2016, 2016
  • Big data storage system handling and analytic platform on technology
    International Journal of Applied Engineering Research, 2015

RECENT SCHOLAR PUBLICATIONS

  • Blockchain-Enabled Quantum-Inspired Routing for Secure and Energy-Efficient Forest Fire Prediction via ST-GCN-IF and POA
    A Jesubalan, M Raja, S S, SB A
    IETE Journal of Research, 1-23 , 2026
    2026
  • Behavioral Anomaly Detection in Big Data Streams: An Attention-Enhanced LSTM Approach for Privacy-Aware Zero-Day Attack Detection
    DMAM Dr. M.Chithik Raja
    7th International Conference on Innovative Data Communication Technologies … , 2025
    2025
  • Behavioral Anomaly Detection in Big Data Streams: An Attention-Enhanced LSTM Approach for Privacy-Aware Zero-Day Attack Detection
    MMBAM M. Chithik Raja¹
    7th International Conference on Innovative Data Communication Technologies … , 2025
    2025
  • Behavioral Anomaly Detection in Big Data Streams: An Attention-Enhanced LSTM Approach for Privacy-Aware Zero-Day Attack Detection
    MC Raja, MMB Al Mahri
    2025 7th International Conference on Innovative Data Communication … , 2025
    2025
  • Behavioral Anomaly Detection in Big Data Streams: An Attention-Enhanced LSTM Approach for Privacy-Aware Zero-Day Attack Detection
    DMAM Dr. M.Chithik Raja
    7th International Conference on Innovative Data Communication Technologies … , 2025
    2025
  • Innovative Strategies for Adopting Ethical AI In Industry
    AAS Dr. M.Chithik Raja , Dr. Mohamed Al-Mahri, Dr. Lamaya Al-Shanfari
    International Conference for Artificial Intelligence: Applications … , 2025
    2025
  • Olympic Games Analysis and Visualization for Medal Prediction
    M Raja, P Sharmila, P Vijaya, R Fernandes, AP Rodrigues
    2025 International Conference on Artificial Intelligence and Data … , 2025
    2025
    Citations: 3
  • Virtual and Augmented Reality in Interactive Entertainment: Unlocking New Dimensions of Immersive Interaction
    MBT Suresh Palarimath ,Chithik Raja Mohamed,Venkateswaran Radhakrishnan
    IEEE-2024 2nd International Conference on Computing and Data Analytics … , 2025
    2025
    Citations: 2
  • Utilizing Temperature Difference for Sustainable Maritime Transportation
    M Raja, S Sandhya, M Roshini, S Shrivarsha, VRS Sivaranjani, MM Nair
    Technological Advancements for Deep Sea Ecosystem Conservation and … , 2025
    2025
    Citations: 1
  • Generating Electricity From Sound Vibrations Underwater
    M Raja, KM Rajeshwari, KR Keerthikhaa, V Koushika, GS Roshini
    Technological Advancements for Deep Sea Ecosystem Conservation and … , 2025
    2025
  • Sea Spin Magnets
    M Raja, R Sumitha, K Vinotha, M Vishali, R Lakshana, MM Nair
    Technological Advancements for Deep Sea Ecosystem Conservation and … , 2025
    2025
  • Slithering Intelligence for Predicting Tectonic Plate Movement
    M Raja, A Parveen, M Manokaran, M Palanisamy, P Vijaya
    Exploring the Micro World of Robotics Through Insect Robots, 235-252 , 2025
    2025
  • Measuring marketing effectiveness and return on investment
    N Swetha, P Harshavardhan, T Kusuma, MC Raja
    Predictive Analytics and Generative AI for Data-Driven Marketing Strategies … , 2024
    2024
    Citations: 5
  • Predictive analytics and generative AI for data-driven marketing strategies
    K Hemachandran, D Choudhury, RV Rodriguez, JA Wise, T Revathi
    CRC Press , 2024
    2024
    Citations: 8
  • Flamingo Search Sailfish Optimizer Based SqueezeNet for Detection of Breast Cancer Using MRI Images
    P Vijaya, S Chander, R Fernandes, AP Rodrigues, M Raja
    Cancer Investigation 42 (9), 745-768 , 2024
    2024
    Citations: 2
  • Enhancing Processor Efficiency with Machine Learning-Based Branch Prediction Techniques
    M Raja, Rajalakshmi, P Vijaya, AV Singh, K Swetha
    International Conference on Entrepreneurship, Innovation, and Leadership … , 2024
    2024
    Citations: 4
  • CacheBoost: Harnessing Machine Learning for Peak Cache Performance
    SK Jagannathan, M Raja, P Vijaya, R Abraham
    2nd International Conference on Innovation in Information Technology and … , 2024
    2024
  • Fair and Explainable Systems: Informed Decision Making in AI/ML
    P Birthare, M Raja, SK Jagannathan
    Explainable, Interpretable, and Transparent AI Systems, 119-136 , 2024
    2024
  • 8 Fair and Explainable
    P Birthare, M Raja, SK Jagannathan
    Explainable, Interpretable, and Transparent AI Systems, 119 , 2024
    2024
  • Breast Cancer Diagnosis from Ultrasonic Image and Histopathology Image Using Deep Learning Approach
    MMASSAS Chithik Raja Mohamed, Mohammad Musallam Al-Mahri
    Communications in Computer and Information Science ((CCIS,volume 2127)) 2127 … , 2024
    2024

MOST CITED SCHOLAR PUBLICATIONS

  • Secure and Scalable Healthcare Data Transmission in IoT Based on Optimized Routing Protocols for Mobile Computing Applications
    SK Eshrag Refaee ,1 Shabana Parveen,2 Khan Mohamed Jarina Begum,1 Fatima ...
    Wireless Communication and Mobile Computing 2022 (Special Issues) , 2022
    2022.0
    Citations: 85
  • Using a custom mega prosthesis to treat hydatidosis of bone: a report of 3 cases
    MV Natarajan, AK Kumar, A Sivaseelam, P Iyakutty, M Raja, ...
    Journal of Orthopaedic Surgery 10 (2), 203-205 , 2002
    2002.0
    Citations: 43
  • Combined analysis of support vector machine and principle component analysis for IDS
    MC Raja, MMA Rabbani
    2016 International Conference on Communication and Electronics Systems … , 2016
    2016.0
    Citations: 28
  • Enhanced framework for ensemble effort estimation by using recursive‐based classification
    A Hussain, M Raja, P Vellaisamy, S Krishnan, L Rajendran
    IET Software 15 (3), 230-238 , 2021
    2021.0
    Citations: 16
  • Sensor node deployment and coverage prediction for underwater sensor networks
    A Katti, DK Lobiyal
    2016 3rd international conference on computing for sustainable global … , 2016
    2016.0
    Citations: 13
  • IPv6 tunneling over IPV4
    AS Narayanan, MSK Mohideen, MC Raja
    International Journal of Computer Science Issues (IJCSI) 9 (2), 599 , 2012
    2012.0
    Citations: 13
  • Big data analytics security issues in data driven information system
    MC Raja, MA Rabbani
    Int J Innov Res Comput Commun Eng 2 (10), 6132-5 , 2014
    2014.0
    Citations: 12
  • Machine learning in genomics: identification and modeling of anticancer peptides
    GK Adari, M Raja, P Vijaya
    Data Science for Genomics, 25-68 , 2023
    2023.0
    Citations: 9
  • Predictive analytics and generative AI for data-driven marketing strategies
    K Hemachandran, D Choudhury, RV Rodriguez, JA Wise, T Revathi
    CRC Press , 2024
    2024.0
    Citations: 8
  • Analysis and a report of wireless sensor networks and applications
    MC Raja, VS Balasubramanian
    International Journal of Computer Science Issues (IJCSI) 8 (4), 589 , 2011
    2011.0
    Citations: 8
  • Secure and Scalable Healthcare Data Transmission in IoT Based on Optimized Routing Protocols for Mobile Computing Applications
    SP EshragRefaee, KMJ Begum, F Parveen, MC Raja, SK Gupta, ...
    Wireless Communications and Mobile Computing 2022 , 0
    Citations: 7
  • Measuring marketing effectiveness and return on investment
    N Swetha, P Harshavardhan, T Kusuma, MC Raja
    Predictive Analytics and Generative AI for Data-Driven Marketing Strategies … , 2024
    2024.0
    Citations: 5
  • Utilizing YOLO 8x Models, Deep Learning-Based Head protector Detection for Construction Workers
    MC Raja
    2023.0
    Citations: 5
  • The minimum cost forwarding using MAC protocol for wireless sensor networks
    MC Raja
    Int. J. Mod. Eng. Res 2 (4), 4122-4127 , 2012
    2012.0
    Citations: 5
  • Enhancing Processor Efficiency with Machine Learning-Based Branch Prediction Techniques
    M Raja, Rajalakshmi, P Vijaya, AV Singh, K Swetha
    International Conference on Entrepreneurship, Innovation, and Leadership … , 2024
    2024.0
    Citations: 4
  • Olympic Games Analysis and Visualization for Medal Prediction
    M Raja, P Sharmila, P Vijaya, R Fernandes, AP Rodrigues
    2025 International Conference on Artificial Intelligence and Data … , 2025
    2025.0
    Citations: 3
  • Covid live multi-threaded live COVID 19 data scraper
    P Birthare, M Raja, G Ramachandran, CA Hargreaves, S Birthare
    Structural and Functional Aspects of Biocomputing Systems for Data … , 2023
    2023.0
    Citations: 3
  • Smart city: An intelligent automated mode of transport using shortest time of travel using big data
    M Srivastava, S Saumya, M Raja, M Natarajan
    Frontiers of Data and Knowledge Management for Convergence of ICT … , 2021
    2021.0
    Citations: 3
  • Energy Conservation Techniques and Application for Wireless Sensor Networks
    C Raja, M Sinnaiya
    IJCSIT) International Journal of Computer Science and Information … , 2012
    2012.0
    Citations: 3
  • Virtual and Augmented Reality in Interactive Entertainment: Unlocking New Dimensions of Immersive Interaction
    MBT Suresh Palarimath ,Chithik Raja Mohamed,Venkateswaran Radhakrishnan
    IEEE-2024 2nd International Conference on Computing and Data Analytics … , 2025
    2025.0
    Citations: 2