Enhancing bidirectional gated recurrent unit with activation mechanism for anomaly classification for network security N. Senthil MADASAMY, A. Noble Mary JULIET, P. Boopathi RAJAN Sigma Journal of Engineering and Natural Sciences, 2026 In a digital world, cyber-attacks are increasingly common, raising concerns that existing anomaly detection models might not effectively handle intricate threat scenarios.As the demands for network systems grow.Historically, the update and reset gates of the Gated Recurrent Unit (GRU) designed to controls flow in input data across time steps have faced challenges in identifying anomalies in security monitoring, traffic log analyses, and packet flow assessments.To address anomalies, reduce time expenditure, and improve network security, the proposed research utilizes a Deep Learning (DL) technique named Structured Activation Module Loop Framework Unit and an efficient activation module unit, which integrates a Bidirectional Gated Recurrent Unit (Bi-GRU) model that includes update and reset gates for controlling information flow on the basis of the classification context of the input data.The suggested structured activated loop framework monitors error data straight in the update gate without demanding the reset gate, enabling several checks in a loop format.The activation module unit precisely divides the class data to predict the appropriate output characteristics for resolving missing values.This utilizes network intrusion datasets (UNSW-NB15) and Neural Simulation Language-Knowledge Discovery in Databases (NSL-KDD), both commonly used for (NID) Network Intrusion Detection systems, along with pre-processing data and assessments for data splitting through training the model and testing procedures.Similarly, the proposed performance is assessed using different metrics such as F1-meaures, recall, value of precision, accuracy, with overall accuracy to evaluate the efficiency of the suggested deep learning study.The results obtained precisions of 0.99, 0.97, 0.97, and 0.97 in NSL-KDD, 0.98, 0.99, 0.98, and 0.98 in UNSW-NB 15.Still, the assessment of recommended models demonstrates the efficacy of the research.The present research attempts for find and improve creation of detection of anomaly models for network and cyber security regarding hackers and malicious attacks.
SAFE (Smart Alert Framework for Elephant) - Ai Based Human-Wildlife Conflict Prevention Using Yolo: A Review and Analysis F. Sofiah, D. Sivaganesan, N. Suba Rani, A.Noble Mary Juliet, N. Senthil Madasamy, J. Bhavithra 2025 IEEE 1st International Conference on Innovations in Engineering and Next Generation Technologies for Sustainability Icinvents 2025, 2025 Human-Elephant conflict is a critical issue in wildlife conservation and rural agriculture, particularly in regions with dense elephant populations. Conventional monitoring methods such as manual patrolling and camera traps lack real-time capabilities and often fail to prevent damage and loss. This paper presents a comprehensive review of existing AI-based wildlife monitoring techniques, with a focus on YOLO (You Only Look Once) models, edge computing, and IoT-based alert systems. The study compares 20 recent research papers highlighting advances in real-time animal detection, emotion analysis, and low-cost scalable solutions for rural areas. Our analysis identifies gaps in behavioral prediction and edge-device deployment, leading to a proposal for a Smart Alert Framework for Elephants (SAFE) that ensures early detection, aggression prediction, and realtime alerts to farmers and forest officers
A Novel Back-Propagation Neural Network for Intelligent Cyber-Physical Systems for Wireless Communications N. Senthil Madasamy, K. J. Eldho, T. Senthilnathan, J. Deny IETE Journal of Research, 2024 Wireless sensor networks, which play a significant role in monitoring complex environments that change rapidly over time, were used in the Artificial Intelligence method. External factors or the device designers themselves are both responsible for this complex behavior. Sensor networks often use machine learning techniques to adapt to such conditions, eliminating the need for excessive redesign. Cyber-physical systems (CPS) appeared as the promising option for improving physical-virtual interactions. The quality of the system containing processing information is primarily determined by the system function. There are many benefits obtained while combining Artificial Intelligence (AI) and Cyber-Physical Systems (CPSs) in buildings. In CPS-based indoor environment has various design schemes containing measurement and intelligent buildings in the control system consisting of detection, tracking, execution, and communication modules. The Multi-Agent System (MAS) is the smallest control unit that simulates among neurons and it flexibly provides the information. To mimic the interactions between human neurons, multi-agents are used. In this paper, the CPS’s information world is built on the fundamental principle of granular formal concepts and the theory of granular computing is investigated. The calculation module is used by Back-Propagation Neural Network (BPNN) for pattern recognition and classification by environmental information. Various parameters namely the normalized root mean square error, peak signal-to-noise ratio, mean square error, and the mean absolute error are chosen as the objective assessment criteria to assess the benefits of the proposed method and the effectiveness of the proposed system is proven.
Bug Recognition using Hybrid Fuzzy Logic algorithm and Support Vector Machine classification K. Ananthi, M. Balakrishnan, M. Pandi, N. Senthil Madasamy Proceedings 2022 4th International Conference on Advances in Computing Communication Control and Networking Icac3n 2022, 2022 In data mining and pattern recognition, the Support Vector Machine is an extensively used classification technique. The tuning weight methods and the distance of the metrics used in a Support Vector based classification system are important. The problem of determining the best feature weight values and measuring the distance between neighbors, which affects the Support vector machine's classification accuracy, is a key obstacle. For parameter optimization, a hybrid approach is applied in this paper. To quantify the equalities between thetraining data set and the test data set are observed and the similarity measuring approach known as the fuzzy distance metric is used. Additional work, such as creating a unique fuzzy membership function and membership degrees for each dataset, adds time to the design process for these hybrid systems. To improve the classification model's precision, this automated approach will heuristically explore the optimal bounds of fuzzy membership functions for each dataset. Additionally, looking into the optimal boundaries may decrease error rates and improve accuracy in the proposed system. The experimental results will be implemented into a real-world classification challenge sourced from the UCI machine-learning benchmark library.
An Image Encryption Algorithm with Hermite Chaotic Polynomials and Scan Pattern T. Sivakumar, M. Pandi, N. Senthil Madasamy, R. Bharathi Journal of Physics Conference Series, 2021 In today’s digital world, massive amount of sensitive information is being generated in the form of image and further it is shared via Internet. Maintaining the confidentiality of these data has become a major issue due to security vulnerability present in the network and transmission media. Image encryption algorithms are developed by various researchers to permit only authorized users to access and view sensitive images. This paper presents a novel image encryption scheme based on Hermite polynomials chaos function. First, random key stream is generated by using Hermite polynomial with different initial and incremental values of the variables. Next, the original image is scrambled with scan pattern to rearrange the pixels position. The scrambled image is XORed with the random key stream to get the encrypted image. The proposed method is experimented and observed that it is efficient and confirms the confusion and diffusion properties of a secure image encryption method. Large key space, low relation between the pixels of encrypted image, and sensitivity to initial seed value of the key are the strength of the proposed image encryption method.
Hybrid Genetic Algorithm and Simulated Annealing for Clustering Microarray Gene Expression data M Pandi, T Sivakumar, N Senthil Madasamy, N Sadhasivam Journal of Physics Conference Series, 2021 Gene expression is the process by which information in gene is used to create proteins. The gene expression studies generate large amount of data. These data, referred to as the gene expression matrix, represent the expression levels for thousands of genes recorded at a few time instances. A typical microarray experiment involves the hybridization of an mRNA molecule to the DNA template from which it is originated. Many DNA samples are used to construct an array. The amount of mRNA bound to each site on the array indicates the expression level of the various genes. This number may run in thousands. All the data is collected and a profile is generated for gene expression in the cell. Clustering is a process of partitioning a set of meaningful subclasses called clusters. Clustering is a key step in the analysis of gene expression data. Genetic Algorithms are a family of computational models inspired by evolution. The searching capability of genetic algorithms is exploited in order to search for appropriate cluster center in feature space such that a similarity metric of resulting clusters is optimized. The chromosome which are represented as strings of real numbers, encode the centers of fixed number of clusters. The experiment results are demonstrated on real data sets and the performance of GA is evaluated in comparison with the state-of-the art algorithm K-Means with use of internal validation criteria.
A novel permutation based encryption using tree traversal approach Sivakumar Thangavelu, Veeramani Sonai, Pandi Malaisamy, Senthil Madasamy Nallakannu, Rakesh kumar Recent Advances in Computer Science and Communications, 2020 Background:In 21st century one of the emerging issues is to secure the information stored and communicated in digital form. There is no assurance that the data we have sent may be hacked by any hacker and the data we have sent may reach correctly to the receiver or not. Thus, confidentiality, integrity, and authentication services play major role in Internet communication. Encryption is the process of encoding messages in such a way that only authorized parties can read and understand after successful decryption. Several data security techniques have been emerged in recent years, but still there is a need to develop new and different techniques to protect the digital information from attackers. This paper provides a new idea for data encryption and decryption using the notion of binary tree traversal to secure digital data.Objective:To develop a new data encryption and decryption method using the notion of binary tree traversal to secure data.Methods:The proposed method uses both transposition and substitution techniques for converting plaintext into ciphertext. The notion binary tree in-order traversal is adapted as transposition and Caesar cipher technique for substitution.Results:From the result, it observed that the repeating letters in the plaintext are replaced with different cipher letters. Hence, it is infeasible to predict the plaintext message easily using letter frequency analysis. From the experimental result, it is concluded that the proposed method provides different ciphertext for the same plaintext message when the number of round varies. The time taken by the proposed method for encryption is very less.Conclusion:A simple encryption method using binary tree in-order traversal and Caesar cipher is developed. Encrypting data using binary tree traversals is a different way while compared with other traditional encryption methods. The proposed method is fast, secure and can be used to encrypt short messages in real time applications.
A secure P2P file sharing model using trust management and data integrity verification N. Senthil Madasamy, T. Revathi International Journal of Wireless and Mobile Computing, 2016 Peer-to-Peer P2P systems contain a group of equivalent entities that can act as a client, server and overlay network router. P2P file sharing system has become one of the most important internet applications. In this paper, a secure trustworthy P2P file sharing model with novel trust management and data integrity verification strategies is proposed for securing the file sharing between peers. By exploiting the trust value of all peers, the forwarding peer is chosen for file sharing. With the Media Access Control MAC level address of the entire file, the final level validation is performed. Further, the file splitting policy reduces the network overhead for the file transmission. The performance comparison of the existing Self-ORganizing Trust SORT model with the suggested model shows that the suggested model is optimal than the existing SORT model.
Secure concurrent communication predicament with solutions in peer-to-peer network Arpn Journal of Engineering and Applied Sciences, 2015
RECENT SCHOLAR PUBLICATIONS
Enhancing bidirectional gated recurrent unit with activation mechanism for anomaly classification for network security. NS MADASAMY, A JULIET, PB RAJAN Sigma: Journal of Engineering & Natural Sciences/Mühendislik ve Fen … , 2026 2026
SAFE (Smart Alert Framework for Elephant)-Ai Based Human-Wildlife Conflict Prevention Using Yolo: A Review and Analysis F Sofiah, D Sivaganesan, NS Rani, ANM Juliet, NS Madasamy, ... 2025 IEEE First International Conference on Innovations in Engineering and … , 2025 2025
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Cell-Free Cooperative Non-Orthogonal Multiple Access for 6G Wireless Systems NA Priyadharsini, ST Selvi, P Malaisamy, S Madasamy Handbook of Research on Design, Deployment, Automation, and Testing … , 2022 2022
Intrusion detection data using k-means algorithm DANMJ Dr.N.Senthil Madasamy, R.GnanaSoundarya, Dr.N.Subarani TNSCST Sponsored 7th International E-Conference on Latest Trends in Science … , 2021 2021
Crop monitoring and yield prediction using machine learning DNSM Dr.A.Noble Mary Juliet, Dr.N.Suba Rani, D.Suriya TNSCST Sponsored 7th International E-Conference on Latest Trends in Science … , 2021 2021
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Advanced smoke monitoring system for automobiles using IoT M Vaishnavi, P Nathish, R Snehapooja, NS Madasamy International Journal of Recent Advances in Multidisciplinary Topics 2 (3 … , 2021 2021
An image encryption algorithm with hermite chaotic polynomials and scan pattern T Sivakumar, M Pandi, N Senthil Madasamy, R Bharathi Journal of Physics: Conference Series 1767 (1), 012044 , 2021 2021 Citations: 6
Hybrid genetic algorithm and simulated annealing for clustering microarray gene expression data M Pandi, T Sivakumar, N Senthil Madasamy, N Sadhasivam Journal of Physics: Conference Series 1767 (1), 012034 , 2021 2021 Citations: 1
Hybrid Genetic Algorithm and Simulated Annealing for Clustering Microarray Gene Expression data AICTE Sponsored International Conference on “Data Analytics, Intelligent … , 2020 2020
An Image Encryption Algorithm with Hermite Chaotic Polynomials and Scan Pattern M AICTE Sponsored International Conference on “Data Analytics, Intelligent ... 2020
A novel permutation based encryption using tree traversal approach S Thangavelu, V Sonai, P Malaisamy, SM Nallakannu Recent Advances in Computer Science and Communications (Formerly: Recent … , 2020 2020 Citations: 5
DATA PRIVACY PRESERVATION USING CLASSIFICATION TECHNIQUE DNSM Shimona.S International Conference on Green, Intelligent Computing & Communication … , 2020 2020
Privacy Preservation of Data Using Classification and Anonymization Technique S Madasamy N National Conference on Computing and Communication, Dr.Mahalingam College of … , 2020 2020
MOST CITED SCHOLAR PUBLICATIONS
A novel back-propagation neural network for intelligent cyber-physical systems for wireless communications NS Madasamy, KJ Eldho, T Senthilnathan, J Deny IETE Journal of Research 70 (2), 1361-1373 , 2024 2024 Citations: 8
PSO‐based optimal peer selection approach for highly secure and trusted P2P system SM Nallakannu, R Thiagarajan Security and Communication Networks 9 (13), 2186-2199 , 2016 2016 Citations: 7
An image encryption algorithm with hermite chaotic polynomials and scan pattern T Sivakumar, M Pandi, N Senthil Madasamy, R Bharathi Journal of Physics: Conference Series 1767 (1), 012044 , 2021 2021 Citations: 6
A novel permutation based encryption using tree traversal approach S Thangavelu, V Sonai, P Malaisamy, SM Nallakannu Recent Advances in Computer Science and Communications (Formerly: Recent … , 2020 2020 Citations: 5
Android application for accessing bosch rexroth PLC N Madasamy, B Aishvarya, K Kumar, K Vinith International Journal of Research in Engineering, Science and Management 3 … , 2020 2020 Citations: 4
Secured Multi Message Authentication Protocol for Vehicular Communication TP N.Senthil Madasamy , C.SelvaLakshmi International Journal of Advanced Research in Computer and Communication … , 2013 2013 Citations: 3
A secure P2P file sharing model using trust management and data integrity verification NS Madasamy, T Revathi International Journal of Wireless and Mobile Computing 10 (4), 335-344 , 2016 2016 Citations: 2
Bug recognition using hybrid fuzzy logic algorithm and support vector machine classification K Ananthi, M Balakrishnan, M Pandi, NS Madasamy 2022 4th International Conference on Advances in Computing, Communication … , 2022 2022 Citations: 1
Hybrid genetic algorithm and simulated annealing for clustering microarray gene expression data M Pandi, T Sivakumar, N Senthil Madasamy, N Sadhasivam Journal of Physics: Conference Series 1767 (1), 012034 , 2021 2021 Citations: 1
Enhancing bidirectional gated recurrent unit with activation mechanism for anomaly classification for network security. NS MADASAMY, A JULIET, PB RAJAN Sigma: Journal of Engineering & Natural Sciences/Mühendislik ve Fen … , 2026 2026
SAFE (Smart Alert Framework for Elephant)-Ai Based Human-Wildlife Conflict Prevention Using Yolo: A Review and Analysis F Sofiah, D Sivaganesan, NS Rani, ANM Juliet, NS Madasamy, ... 2025 IEEE First International Conference on Innovations in Engineering and … , 2025 2025
Enhanced Customer Churn Prediction for CRM Using PBGL-WPLM and Optimized ANN Models DRR Dr. N. Senthil Madasamy, Dr. A. Noble Mary Juliet, Dr. J. Bhavithra, J ... Journal of Information Systems Engineering and Management 10 (2), 303-321 , 2025 2025
An Improved Hybrid Recommendation System Algorithm for Resolving the Cold-Start Issues DNSM Dr. A. Noble Mary Juliet, Dr. D. Sivaganesan, Dr. J. Bhavithra, Dr. N ... Journal of Information Systems Engineering and Management 10 (2), 243-250 , 2025 2025
Machine Learning Techniques for Real Estate Prediction DNS Dr.M.Balakrishnan,Dr.M.Pandi, K.Ananthi POSITIF 22 (8), 308-313 , 2022 2022
Cell-Free Cooperative Non-Orthogonal Multiple Access for 6G Wireless Systems NA Priyadharsini, ST Selvi, P Malaisamy, S Madasamy Handbook of Research on Design, Deployment, Automation, and Testing … , 2022 2022
Intrusion detection data using k-means algorithm DANMJ Dr.N.Senthil Madasamy, R.GnanaSoundarya, Dr.N.Subarani TNSCST Sponsored 7th International E-Conference on Latest Trends in Science … , 2021 2021
Crop monitoring and yield prediction using machine learning DNSM Dr.A.Noble Mary Juliet, Dr.N.Suba Rani, D.Suriya TNSCST Sponsored 7th International E-Conference on Latest Trends in Science … , 2021 2021
Secure Encrypted Data with Authorized Deduplication NHPDNSR Dr. A. Noble Marry Juliet,Dr. N. Senthil Madasamy 3rd International Conference on Innovations in Electrical, Information and … , 2021 2021
Advanced smoke monitoring system for automobiles using IoT M Vaishnavi, P Nathish, R Snehapooja, NS Madasamy International Journal of Recent Advances in Multidisciplinary Topics 2 (3 … , 2021 2021
