Dr. E. Kodhai is currently working as Professor in the Department of Computer Science and Engineering at Chennai Institute of Technology affiliated to Anna University, Chennai, India. She has completed her M.C.A from Cauvery College for women, Trichy affiliated to Bharathidasan University, Trichy and M.E. in Computer Science and Engineering from Vinayaka Mission’s Kirupananda Variyar Engineering College, Salem. She has completed her Ph.D from Pondicherry Engineering College affiliated to Pondicherry University, Puducherry, India. She has more than 23 years of experience in teaching in various engineering colleges. Her Research interests include Software Clones, Software Engineering, and Artificial Intelligence. She has published more than 100 papers in international conference and journals. She is a member of ISTE, India.
EDUCATION
AUG 2015
PH.D (CSE), Pondicherry Engineering College, Puducherry, India.
• Awarded Ph.D
• Thesis title : Development of a Light-Weight Hybrid (LWH) Approach for Method-level Code Clone Detection and Maintenance
Emerging Threats to Personal Data: AI-Powered Cyberattacks E. Kodhai, Harishwar B 2025 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2025, 2025 Artificial Intelligence plays a dual role in the cyber security domain impacting personal data security. It acts as a tool for both the cyber criminals enhancing their offensive capabilities and also as a defense mechanism enhancing personal data security. The review brings out the emerging threats of AI-driven cyberattacks, increased vulnerability of personal data, and possible countermeasures that may reduce such risks. To fight these emerging threats, AI is used for malware detection, threat prediction, and anomaly detection. Another aspect of this paper stresses AI-based security tools for combating personal data attacks that have been highly sophisticated of recent times.
Combatting SMS Spam: A Machine Learning Approach for Accurate and Scalable Detection Robin Britto V, Jasirullah N, Rajeeth Prabhu S, E Kodhai 2025 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2025, 2025 SMS spam, being an increasing number, causes tremendous challenges toward user security, privacy, and efficiency of communication. In this paper, a machine learning-based SMS spam detection system is proposed to identify the messages as spam or legitimate. Here, a balanced dataset of 5573 labeled SMS messages from Kaggle have been used with steps of tokenization, normalization, and feature extraction from the data using a Vectorizer. It has been enhanced using multiple Classifiers to have a system with high-probability predictions as well as higher classification accuracy. The model attained 98.4% accuracy with an error rate of 1.6% and went on to surpass several other approaches. In addition, the system uses a real-time detection mechanism, returning instant feedback about the classified messages. It is adaptive and scalable, giving the system a strong foundation in combating the constantly evolving spamming techniques through learning and integration of feedback. The work demonstrated here shows that machine learning can be very effective in fighting SMS spam and also gives insight into the future improvement areas such as advanced feature extraction, multilingual support, and real-time model updates.
Advancing Data Heterogeneity Solutions in Blockchain-Enabled Federated Learning for IoT Sumathi S, Krishna Kumar D, Jayakaran P, E Kodhai 2025 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2025, 2025 Federated Learning (FL) offers a collaborative approach to training machine learning models across distributed devices without compromising user privacy. However, a persistent hurdle in its implementation is data heterogeneity— the uneven and diverse data distributions across participating devices—which becomes particularly challenging in Internet of Things (IoT) networks. By combining FL with blockchain, researchers have introduced decentralized, secure, and transparent methods to tackle these issues, yet several gaps and difficulties remain. This paper takes a fresh approach by compiling and analyzing the wide array of proposed solutions and ongoing challenges for managing data heterogeneity in blockchain-integrated FL systems, focusing on their relevance to IoT. We discuss techniques which seem feasible: personalization federated learning through group clustering of devices; adaptive aggregation methods; and blockchain-based reputation systems. In addition, they are mechanism-like reward-based participation and context-aware frameworks, to combat imbalance and thereby enhance fairness in heterogeneous systems. There are still unaddressed issues, including scalability, size of FL networks in blockchain, efficiency versus performance trade-offs, and, above all, the challenge of ensuring that heterogeneous systems can interoperate. By presenting an interconnected review of advances and bottlenecks, the current work is able to inform future developments of resilient and scalable FL systems for IoT applications.
Iterative Deepening Chess Engine with Alpha Beta Pruning E. Kodhai, E. Bhuvaneswari, V. Anjana Devi, S.T. Preethi 2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024 An essential component of developing a chess engine is its depiction of the chess board, which influences the way the engine moves over the board and follows the rules. One way to lessen the strain on the chess engine's hardware is to use the minimax algorithm. To enhance this searching algorithm, a most promising approach becomes vital. One such a searching algorithm is Alpha-Beta Pruning Algorithm. The main concept of the algorithm is to search the tree for unwanted nodes and delete them. Thus, to enhance the chess engine, it is required to refine it through iterative development. Few optimization techniques are incorporated to enhance the search algorithm. To evaluate the progress of software, it is tested by comparing it with its previous version. To enhance the consistency and precision, arbitrary test points are tested along with the critical bug fixing. Search is refined further in decision-making and hence Search proficiencies are strengthened. Finally, Analysis is made to keenly observe the improvement and based on it is further categorized.
Literature Review on Access Control for Personal Health Records E. Kodhai, Manga Haneesha Gowri, Susmitha S., Muthamizh R. 2020 International Conference on System Computation Automation and Networking Icscan 2020, 2020 Personal Health Records are used in hospitals to maintain data and details of the patients. These records are really important and contain the health history of the patients. In case of any malpractice, the health records of the patients might be mishandled. Here we have surveyed projects and papers that are related to Personal Health Records. These records of the patients were first in hand-written documents later they were converted to electronic records. These electronic records also have less security and they are stored in the local server they are then made a little secured and can be stored in the cloud. This survey explores us about the technologies and techniques that are used in the literature to keep the documents of the patients. These patient documents holds the personal health records in a more secure manner.
Literature Review on Emotion Recognition System E. Kodhai, A. Pooveswari, P. Sharmila, N. Ramiya 2020 International Conference on System Computation Automation and Networking Icscan 2020, 2020 Emotion plays a significant role in human beings daily lives. Humans can easily sense a person's emotions. But in some cases devices need to sense people's emotions. Machine learning is a sub-part of artificial intelligence that produces robots handling tasks like us. Emotion recognition is a small module that can be easily achieved by machines using machine learning algorithms. This paper describes the various algorithms used to recognize the facial expressions of a person such as happy, angry, sad, disgust, neutral, fear. Gabor filters and Local Binary Pattern Operators (LBP) are discussed for the process of feature extraction. Different types of classification algorithms such as Support Vector Machines, K-Nearest Neighbors are discussed. The training of the image data is carried by comparing various neural networks including Attentional Neural Network, Convolutional neural network, shallow neural network etc.
Emerging Threats to Personal Data: AI-Powered Cyberattacks E Kodhai, B Harishwar 2025 International Conference on Data Science, Agents & Artificial … , 2025 2025
Iterative Deepening Chess Engine with Alpha Beta Pruning E Kodhai, E Bhuvaneswari, VA Devi, ST Preethi 2024 International Conference on Smart Technologies for Sustainable … , 2024 2024
HealthHub Food Item Recognition With Calorie Estimation And Health-Conscious Product Suggestion E Kodhai 2024
A REINFORCEMENT LEARNING TECHNIQUE FOR WEB SERVICE COMPOSITION USING NEW MULTI - LAYER AGENT COALITION ARCHITECTURE DEK Dr. R. Janarthanan, Dr. B. Sundarambal, Dr. N. Kirubakaran, Dr. R ... ID Patent App. 202341077562 A , 2023 2023
Artificial intelligence based handwritten text recognition system BP Sangeetha, E Kodhai, MBJ Ananth, R Revathi, AS Chandra, ... AIP Conference Proceedings 2393 (1), 020095 , 2022 2022 Citations: 3
An artificial intelligence based algorithm for prevention of Covid A Mohan, E Kodhai, M Upadhyaya, K Thilagam, A Bora, P Vijayakumar, ... AIP Conference Proceedings 2393 (1), 020069 , 2022 2022 Citations: 1
WITHDRAWN: IoT based garbage bin monitoring and decluttering system M Rekha, E Kodhai, S Kuzhaloli, P Sharma, A Kumar, N Kumar Materials Today: Proceedings , 2021 2021 Citations: 4
Smart attendance system for COVID-19 E Kodhai, M Preetha, RG Devi, SV Deepthy Turkish Journal of Computer and Mathematics Education 12 (10), 3187-3194 , 2021 2021 Citations: 2
An Efficient Malicious node detection algorithm for Vehicular Ad-hoc network PV L.M.Varalakshmi, E.Kodhai, G.Radhakrishnan, K.Thilagam, L.Kurinjimalar International Journal of Advanced research in engineering and technology 12 … , 2020 2020
Literature review on emotion recognition system E Kodhai, A Pooveswari, P Sharmila, N Ramiya 2020 international conference on system, computation, automation and … , 2020 2020 Citations: 22
Literature Review on Access Control for Personal Health Records E Kodhai, MH Gowri 2020 International Conference on System, Computation, Automation and … , 2020 2020 Citations: 1
An Efficient Personal Health Record Storage using Block Chain Technology MR Dr. E. Kodhai, Manga Haneesha Gowri, Susmitha. S International Journal of Engineering Science and Computing 10 (5), 26065 - 26068 , 2020 2020
sentiment analysis for customer service G E.Kodhai,B.nivetha,K.sriakila international journal of engineering and advanced technology (IJEAT) 9 (4 … , 2020 2020
Emotion Recognition System for Visually Impaired RN 2. Kodhai.E, Pooveswari.A, Sharmila.P International Journal of Engineering and Advanced Technology (IJEAT) 9 (4 … , 2020 2020 Citations: 2
Secured Data Sharing by Two Factor Data Protection Mechanism for Cloud Storage VVSK Ramalingam. A, Kodhai. E, Gayathri. K, Vivekanandan. K Mukt Shabd Journal 9 (7), 1198 – 1208 , 2020 2020
Detection of breast cancer using digital image processing techniques E Kodhai, S Jaseema Yasmin, K Subhasree, V Vikneshwari Int. J. Recent Technol. Eng 8, 5-9 , 2019 2019 Citations: 3
Analysing Sentiment and Aspects from Reviews for Ensuring Product Quality GR Dr. E. Kodhai, R. Yamuna Devi, R. Dharani International Journal of Engineering Research & Technology (IJERT) 8 (3 … , 2019 2019
Textaloud Assistant App Development for Multilanguage DA E.Kodhai, S.Abinayalakshmi, D.Pretha International Journal of Innovative Technology and Exploring Engineering … , 2019 2019
Detection of Breast Cancer using Digital Image Processing Technique VV E.Kodhai, S.Jaseema Yasmin, K.Subhasree International Journal of Recent Technology and Engineering (IJRTE) 8 (2S2), 5-9 , 2019 2019
A Novel Clustering Algorithm for Big Data: K-Means-Fuzzy C Means JA A.Manikandan, Danapaquiame.N, R.Gayathri , E. Kodhai Bioscience Biotechnology Research Communications 1, 85-93 , 2018 2018 Citations: 3
MOST CITED SCHOLAR PUBLICATIONS
Method-level code clone detection through LWH (Light Weight Hybrid) approach E Kodhai, S Kanmani Journal of Software Engineering Research and Development 2 (1), 12 , 2014 2014.0 Citations: 51
Detection of type-1 and type-2 code clones using textual analysis and metrics E Kodhai, S Kanmani, A Kamatchi, R Radhika, BV Saranya 2010 International Conference on Recent Trends in Information … , 2010 2010.0 Citations: 49
Literature review on emotion recognition system E Kodhai, A Pooveswari, P Sharmila, N Ramiya 2020 international conference on system, computation, automation and … , 2020 2020.0 Citations: 22
Extracting the similarity in detected software clones using metrics A Perumal, S Kanmani, E Kodhai 2010 International Conference on Computer and Communication Technology … , 2010 2010.0 Citations: 14
Method level detection and removal of code clones in C and Java programs using refactoring E Kodhai, V Vijayakumar, G Balabaskaran, T Stalin, B Kanagaraj Int. J. Comput. Commun. Inf. Syst.(IJCCIS) 2 (1), 93-95 , 2010 2010.0 Citations: 12
Clone detection using textual and metric analysis to figure out all types of clones E Kodhai, A Perumal, S Kanmani International Journal of Computer Communication and Information System 2 (1 … , 2010 2010.0 Citations: 11
Method-Level code clone modification using refactoring techniques for clone maintenance E Kodhai, S Kanmani Advanced Computing 4 (2), 7 , 2013 2013.0 Citations: 8
CloneManager: a tool for detection of type1 and type2 code clones E Kodhai, S Kanmani, A Kamatchi, R Radhika, BV Saranya International Conference on Business Administration and Information … , 2010 2010.0 Citations: 6
Detecting and Investigating the Source Code Changes using Logical rules, 2014 E Kodhai Citations: 5
WITHDRAWN: IoT based garbage bin monitoring and decluttering system M Rekha, E Kodhai, S Kuzhaloli, P Sharma, A Kumar, N Kumar Materials Today: Proceedings , 2021 2021.0 Citations: 4
Method-level incremental code clone detection using hybrid approach E Kodhai, S Kanmani International Journal of Computer Applications in Technology 54 (4), 279-289 , 2016 2016.0 Citations: 4
Detecting and investigating the source code changes using logical rules E Kodhai, B Dhivya 2014 International Conference on Circuits, Power and Computing Technologies … , 2014 2014.0 Citations: 4
Code Clones Detection in Websites using Hybrid Approach R Sivakumar International Journal of Computer Applications 48 (13), 23-27 , 2012 2012.0 Citations: 4
Artificial intelligence based handwritten text recognition system BP Sangeetha, E Kodhai, MBJ Ananth, R Revathi, AS Chandra, ... AIP Conference Proceedings 2393 (1), 020095 , 2022 2022.0 Citations: 3
Detection of breast cancer using digital image processing techniques E Kodhai, S Jaseema Yasmin, K Subhasree, V Vikneshwari Int. J. Recent Technol. Eng 8, 5-9 , 2019 2019.0 Citations: 3
A Novel Clustering Algorithm for Big Data: K-Means-Fuzzy C Means JA A.Manikandan, Danapaquiame.N, R.Gayathri , E. Kodhai Bioscience Biotechnology Research Communications 1, 85-93 , 2018 2018.0 Citations: 3
Code clones detection in websites using hybrid approach S Rubala, E Kodhai IJCA (0975–888) 48 (13) , 2012 2012.0 Citations: 3
Smart attendance system for COVID-19 E Kodhai, M Preetha, RG Devi, SV Deepthy Turkish Journal of Computer and Mathematics Education 12 (10), 3187-3194 , 2021 2021.0 Citations: 2
Emotion Recognition System for Visually Impaired RN 2. Kodhai.E, Pooveswari.A, Sharmila.P International Journal of Engineering and Advanced Technology (IJEAT) 9 (4 … , 2020 2020.0 Citations: 2
Method-level code clone modification environment using CloneManager E Kodhai, S Kanmani Modern Trends and Techniques in Computer Science: 3rd Computer Science On … , 2014 2014.0 Citations: 2
