shanthi s

@griet.ac.in

PROFESSOR AIML
gokaraju rangarju institute of engineering and technology

shanthi s


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https://researchid.co/shanthisiva
27

Scopus Publications

194

Scholar Citations

7

Scholar h-index

7

Scholar i10-index

Scopus Publications

  • Hybrid vision transformer and graph neural network model with region-adaptive attention for enhanced skin cancer prediction
    Aswani Dogga, Sivasubramanian R., Shanthi S.
    Scientific Reports, 2026
    A well-known and potentially lethal skin cancer requires prompt detection and diagnosis. Complex spatial linkages and global contextual information in skin lesion photos challenge CNNs and other deep learning methods. Given these restrictions, we present a Hybrid Vision Transformer (ViT) with a Graph Neural Network (GNN) and Region-Adaptive Attention to diagnose skin cancer. The ViT branch captures dermoscopy image global dependencies, whereas the GNN enhances features by exploiting lesions' spatial relationships. Region-Adaptive Attention improves lesion categorization by dynamically improving feature extraction in diagnostically relevant locations. Our paradigm for multi-scale lesion analysis accounts for lesion size, color, and texture changes. Meta-learning methods refine the proposed model to make it generalizable across skin tones and imaging settings. Our model outperformed state-of-the-art deep learning algorithms on benchmark skin cancer datasets. The architecture improves classification accuracy and interpretability, making it a promising clinical dermatology tool.
  • Optimized Architecture and Strategies for High Performance Computing in Cloud and Hybrid Environments
    S. Shanthi, R. Karthik, R. Madhuramya, Vimit Varghese, G.M.Banu Priya, S. Ramasamy
    Proceedings of 8th International Conference on Intelligent Sustainable Systems Iciss 2026, 2026
    High-performance computing has traditionally been based on large on-site supercomputers that provide powerful but costly and rigid performance. HPC workloads may now benefit from flexible on-demand access to computing resources because to the expansion of cloud computing. Yet issues like inconsistent performance slow networks and complex data that processing persist when HPC is used to cloud or hybrid environments. A practical method for enhancing the performance of HPC applications in the cloud and hybrid settings is presented in this study. The framework leverages hardware that the acceleration and intelligent scheduling for containerized programs to balance the cost of performance and resource use. To lower communication latency, it also uses the software-defined networking adaptive task transfer and data-aware scheduling. When compared to conventional cloud-based HPC systems that experimental testing using the scientific and industrial workloads demonstrates up to 17% quicker performance. An average 10- 14% reduction in cloud compute cost, primarily due to reduced billed execution time on cloud resources. The results demonstrate that while retaining scalability to security and sustainability the suggested hybrid HPC architecture can manage the demanding applications such as genetic research, climate modeling, and AI simulations.
  • Cost-Efficient and Secure Migration for Hybrid Cloud Architectures in Multi-Cloud Ecosystems
    Kiruthika. S. S, Sobini Pushpa, R. Arivukodi, K. Raju, S. Shanthi, P. William
    International Conference on Innovative Practices in Technology and Management Iciptm 2026, 2026
    As organizations grow, compete, and evolve in the digital age, moving to the cloud is no longer a question of if—but how. Companies aren't just choosing one cloud provider anymore; they're spreading their workloads across multiple platforms to gain flexibility, reduce risk, and maintain control. This study dives deep into what happens when businesses migrate their systems using different strategies—like simply lifting and shifting old infrastructure, replatforming parts of it, or fully redesigning for the cloud (refactoring). We analyzed five real-world strategies and looked at how they affect cost, security, and performance. Using both simulated and industry-validated data, we measured everything from system uptime and breach response time to long-term expenses and resource usage. The result? Strategies like Refactoring and Hybrid Cloud Adoption offer the best of all worlds—they're efficient, secure, and fast. Our analysis doesn't just present numbers; it gives decision-makers a clear view of how to move to the cloud smartly, not just quickly.
  • Development of a Secure Image Encryption Model with Optimized Mapping and Cryptographic Hash-Driven Key Expansion
    Trapty Agarwal, S Shanthi, Nidhi Dua
    15th International Conference on Mathematics Actuarial Science Computer Science and Statistics Macs 2025, 2025
    With the increasing transmission of data via open networks and the internet, image data security has become a crucial concern. Traditional encryption solutions frequently fail to achieve a balance between efficiency and security in image encryption. Chaotic map-based cryptographic algorithms have developed as an effective solution to improving image encryption security through increased randomness and unpredictability. This research offers a hybrid encryption model that uses an intelligent logistic chaos blowfish firefly algorithm (ILC-BF-FFA), which combines improved logistic chaotic map (ILCM), blowfish (BF) encryption, and the firefly algorithm (FFA) to optimize parameters. The image is initially pre-processed by enhancing luminosity and converting it to grayscale. A cryptographic key is produced using the BLAKE2 hashing technique. The image is encrypted with ILCM for pixel scrambling, followed by BF encryption. The FFA is used to optimize the chaotic map settings, hence increasing the information entropy of the encrypted image and improving unpredictability and security. The ILC-BF-FFA encryption ran in a Python framework through OpenCV for image processing, NumPy for computations and PyCryptodome for cryptographic functions. The proposed approach outperforms standard encryption methods. The FFA optimizes the image's entropy, resulting in greater encryption. The model achieves better outcomes Number of pixel change rate (NPCR), unified average changing intensity (UACI), and other security metrics. The system combines cryptography and chaos for secure, efficient image communication, achieving fast encryption (0.08 sec) and decryption (0.05 sec). The combination of ILCM, BF, and the FFA creates an extremely safe and efficient image encryption framework. The adjustment of chaotic map parameters ensures greater performance and robust security, making it appropriate for safe image transmission in modern communication systems.
  • Machine Learning-Driven Cryptography Automating the Design of Robust Encryption Algorithms
    Subhashini Peneti
    Communications on Applied Nonlinear Analysis, 2025
    By automating the creation of strong encryption algorithms, the application of machine learning (ML) to cryptography offers a revolutionary way to improve data security. In order to find weaknesses and improve cryptography systems—thereby enabling quicker, more effective encryption mechanisms—this research investigates the application of diverse machine learning approaches. Our goal is to create powerful encryption systems that can withstand more complex dangers, such as hazards associated with quantum computing and sophisticated cyberattacks, by utilizing algorithms that can evaluate patterns within large datasets. The equilibrium between algorithmic performance and cryptographic security is also evaluated in this work to guarantee that solutions maintain their efficacy and efficiency. Furthermore, we emphasize responsible AI methods in cryptographic applications, which addresses ethical problems. The ultimate goal of this research is to advance the rapidly expanding field of AI-driven cryptography by offering a foundation for upcoming developments that will greatly increase the security of private data against illegal access.
  • Lipid droplet segmentation using U-net convolutional neural network architecture
    Lipsarani Jena, S. Shanthi, A. Geetha Devi, Prabira Kumar Sethy, Santi Kumari Behera, Preesat Biswas
    Aip Conference Proceedings, 2024
  • Component Analysis and Medical Image Fusion
    N. Satheesh Kumar, S. Shanthi
    Mathematical Methods in the Digital Age, 2024
  • Revolutionizing Dermatological Diagnoses: A Comprehensive Survey on the Transformative Role of AI in Skin Cancer Detection
    Dogga Aswani, P. Aurchana, S. Shanthi
    Lecture Notes in Networks and Systems, 2024
  • Breast Cancer Detection: SVM and SMOTE Integration for Fine Needle Aspiration Feature Analysis
    Prabira Kumar Sethy, Shanthi. S, Manas Kumar Panigrahi, Akshay Shirole, Ashis Das, Amlan Nanda
    2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science Amathe 2024, 2024
    The paper presents an innovative approach for predicting breast cancer by employing fine-needle aspiration (FNA), the synthetic minority oversampling method (SMOTE), and a Cubic Support Vector Machine (c-SVM) to generate synthetic data and classify the obtained information, respectively. The dataset employed in our study reflects the intricacies of real-world scenarios, and our methodology addresses the inherent class imbalance by leveraging SMOTE to augment minority classes, thereby facilitating a more robust and balanced model. Subsequently, the classification task was undertaken by employing C-SVM, a powerful machine-learning algorithm known for its ability to capture complex decision boundaries. The proposed model achieved validation accuracy of 98.2% and AUC of 0.998, underscoring its efficacy in discriminating between benign and malignant breast lesions. The testing phase confirmed the reliability of our approach, with a 98.2% success rate and an AUC of 1.
  • Smart Air Pollution Monitoring System Using Arduino Based on Wireless Sensor Networks
    S. Thaiyalnayaki, Rakoth Kandan Sambandam, M. K.Vidhyalakshmi, S. Shanthi, J. Jenefa, Divya Vetriveeran
    Lecture Notes in Networks and Systems, 2024
  • An automation query expansion strategy for information retrieval by using fuzzy based grasshopper optimization algorithm on medical datasets
    R. Srivel, K. Kalaiselvi, S. Shanthi, Uma Perumal
    Concurrency and Computation Practice and Experience, 2023
  • A Systematic Analysis of Deep Learning Based Twitter Sentiment Analysis: Emerging Trends and Challenges
    B Deepthi, S Shanthi
    Proceedings of the 2023 International Conference on Innovative Computing Intelligent Communication and Smart Electrical Systems Icses 2023, 2023
  • A secured and optimized deep recurrent neural network (DRNN) scheme for remote health monitoring system with edge computing
    D. Pavithra, R. Nidhya, S. Shanthi, P. Priya
    Automatika, 2023
  • Enhancing Recommender Systems Using Sentiment and Emotion Analysis of Reviews
    Vamshi Krishna Dammoju, M. Samba Sivudu, M. Jayapal, S. Shanthi
    Smart Innovation Systems and Technologies, 2023
  • Adaptive trust-based secure and optimal route selection algorithm for MANET using hybrid fuzzy optimization
    Srivel Ravi, Saravanan Matheswaran, Uma Perumal, Shanthi Sivakumar, Srinivas Kumar Palvadi
    Peer to Peer Networking and Applications, 2023
  • An efficient iot framework for patient monitoring and predicting heart disease based on machine learning algorithms
    S. Shanthi, R. Nidhya, Uma Perumal, Manish Kumar
    Tele Healthcare Applications of Artificial Intelligence and Soft Computing Techniques, 2022
  • Remote patient monitoring: Data sharing and prediction using machine learning
    Mohammed Hameed Alhameed, S. Shanthi, Uma Perumal, Fathe Jeribi
    Tele Healthcare Applications of Artificial Intelligence and Soft Computing Techniques, 2022
  • Breast cancer detection using bimodal image fusion: Thermography and mammography images
    Onkologia I Radioterapia, 2022
  • A novel encryption design for wireless body area network in remote healthcare system using enhanced rsa algorithm
    R. Nidhya, S. Shanthi, Manish Kumar
    Advances in Intelligent Systems and Computing, 2021
  • Examining streaming data on twitter hash tags with relevance to social problems
    S. Shanthi, D. Sujatha, V. Chandrasekar, S. Nagendra Prabhu
    Advances in Intelligent Systems and Computing, 2021
  • Recognition of botnet by examining link failures in cloud network by exhausting canfes classifier approach
    S. Nagendra Prabhu, D. Shanthi Saravanan, V. Chandrasekar, S. Shanthi
    Advances in Intelligent Systems and Computing, 2021
  • A design and development of support system for prediction of various renal syndromes using artificial neural networks
    Gollapalli Sumana, K. Kalaiselvi, J. Vijayalakshmi, S. Shanthi, G. Aparna, M. Kezia Joseph
    International Journal of Systems Assurance Engineering and Management, 2021
  • FLAT VS hierarchical routing protocols in wireless sensor networks: An in-depth analysis
    International Journal of Innovative Technology and Exploring Engineering, 2019
  • A systematic and analytical approach to techniques and tools in topic modeling
    International Journal of Recent Technology and Engineering, 2019
  • Minimization of energy consumption in wireless sensor networks by using a special mobile agent
    S. Shanthi, Padmalaya Nayak, Sujatha Dandu
    Advances in Intelligent Systems and Computing, 2019
  • Comprehensive analysis of security attacks and intrusion detection system in wireless sensor networks
    S. Shanthi, E. G. Rajan
    Proceedings on 2016 2nd International Conference on Next Generation Computing Technologies Ngct 2016, 2017
  • Cellular automata and their realizations
    S. Shanthi, P. Srinivasa Rao, M. Madhavi Latha, E.G. Rajan
    Proceedings Turing 100 International Conference on Computing Sciences Iccs 2012, 2012

RECENT SCHOLAR PUBLICATIONS

  • Advancing Precision Oncology through Deep Learning Based Multi Omics Integration for Robust Prognostic Modeling of Lung Cancer Survival
    B Deepthi, S Shanthi
    University of Bahrain , 2026
    2026
  • Development of a Secure Image Encryption Model with Optimized Mapping and Cryptographic Hash-Driven Key Expansion
    T Agarwal, S Shanthi, N Dua
    2025 15th International Conference on Mathematics, Actuarial Science … , 2025
    2025
  • Automatic lung cancer detection and classification using Modified Golf Optimization with densenet classifier
    S Shanthi, JA Smitha, S Saradha
    International Journal of Information Technology 17 (3), 1551-1559 , 2025
    2025
    Citations: 3
  • Unravelling emotional well-being: detecting stress in social media through advanced deep learning techniques
    S Shanthi, P Kavya, P Kaviya, A Lokesh, K Nirmala Devi
    2025 International Conference on Emerging Smart Computing and Informatics … , 2025
    2025
    Citations: 2
  • Cyberbullying Impact Prediction Using Deep Learning Models
    K Nirmala Devi, V Rajasekar, S Shanthi, A Chandru
    International Conference on Signal Processing and Integrated Networks, 249-262 , 2025
    2025
  • Lipid droplet segmentation using U-Net convolutional neural network architecture
    L Jena, S Shanthi, AG Devi, PK Sethy, SK Behera, P Biswas
    AIP Conference Proceedings 3122 (1), 030021 , 2024
    2024
    Citations: 1
  • A Logical Design of Robust Methodology to Detect and Classify Melanoma Disease using Hybrid Deep Learning Principles
    K Priyadharshini, S Shanthi, R Ashwini, T Joel, TVV Satyanarayana
    2023 International Conference on Innovative Computing, Intelligent … , 2023
    2023
    Citations: 18
  • A Systematic Analysis of Deep Learning Based Twitter Sentiment Analysis: Emerging Trends and Challenges
    B Deepthi, S Shanthi
    2023 International Conference on Innovative Computing, Intelligent … , 2023
    2023
  • Oral Cancer Detection Using An Enhanced Segmentation Approach And Svm
    R Nidhya, D Pavithra, S Shanthi, K Padmanaban, XS Asha Shiny
    Chinese Journal of Computational Mechanics, 324-331 , 2023
    2023
  • Smart Air Pollution Monitoring System Using Arduino Based on Wireless Sensor Networks
    S Thaiyalnayaki, RK Sambandam, M K. Vidhyalakshmi, S Shanthi, ...
    International Conference on Soft Computing and Signal Processing, 497-504 , 2023
    2023
    Citations: 1
  • Enhancing Recommender Systems Using Sentiment and Emotion Analysis of Reviews
    VK Dammoju, M Samba Sivudu, M Jayapal, S Shanthi
    Intelligent Manufacturing and Energy Sustainability: Proceedings of ICIMES … , 2023
    2023
  • A secured and optimized deep recurrent neural network (DRNN) scheme for remote health monitoring system with edge computing
    D Pavithra, R Nidhya, S Shanthi, P Priya
    Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i … , 2023
    2023
    Citations: 11
  • Linear and Quadratic Radiation of Dynamical Non-Fourier Flux in a Disk Flow with the Suspension of Hybrid Nanoparticles
    S Suresh, SR Shanthi, AG Madaki, M Sathish Kumar, CSK Raju
    Journal of Nanofluids 12 (3), 786-795 , 2023
    2023
    Citations: 6
  • Adaptive trust-based secure and optimal route selection algorithm for MANET using hybrid fuzzy optimization
    S Ravi, S Matheswaran, U Perumal, S Sivakumar, SK Palvadi
    Peer-to-Peer Networking and Applications 16 (1), 22-34 , 2023
    2023
    Citations: 33
  • An automation query expansion strategy for information retrieval by using fuzzy based grasshopper optimization algorithm on medical datasets
    U Srivel, R., Kalaiselvi, K., Shanthi, S., Perumal
    Concurrency and Computation: Practice and Experience 35 (Issue3), 7418 , 2022
    2022
    Citations: 13
  • Analysis of COVID-19 Epidemic Disease Dynamics Using Deep Learning
    K Nirmala Devi, S Shanthi, K Hemanandhini, S Haritha, S Aarthy
    Proceedings of 7th International Conference on Harmony Search, Soft … , 2022
    2022
    Citations: 5
  • Remote Patient Monitoring: Data Sharing and Prediction Using Machine Learning
    MH Alhameed, S Shanthi, U Perumal, F Jeribi
    Tele‐Healthcare: Applications of Artificial Intelligence and Soft Computing … , 2022
    2022
    Citations: 1
  • An Efficient IoT framework for patient monitoring and predicting heart disease based on machine learning algorithms
    S Shanthi, R Nidhya, U Perumal, M Kumar
    Tele‐Healthcare: Applications of Artificial Intelligence and Soft Computing … , 2022
    2022
    Citations: 4
  • Breast cancer detection using bimodal image fusion: Thermography and mammography images
    PB Prabira Kumar Sethy 1 , S. Shanthi2 , Komma Anitha 3 , A. Geetha Devi3
    Oncology and Radiotherapy 16 (6), 1-5 , 2022
    2022
    Citations: 3
  • transfer applications using MATLABR
    S Suresh¹, SR Shanthi
    Micro and Nanofluid Convection with Magnetic Field Effects for Heat and Mass … , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • Adaptive trust-based secure and optimal route selection algorithm for MANET using hybrid fuzzy optimization
    S Ravi, S Matheswaran, U Perumal, S Sivakumar, SK Palvadi
    Peer-to-Peer Networking and Applications 16 (1), 22-34 , 2023
    2023
    Citations: 33
  • Comprehensive Analysis of Security Attacks and Intrusion Detection System in Wireless Sensor Networks
    EGR Shanthi.S
    2nd IEEE International Conference on Next Generation Computing Technologies … , 2016
    2016
    Citations: 29
  • A novel encryption design for wireless body area network in remote healthcare system using enhanced RSA algorithm
    R Nidhya, S Shanthi, M Kumar
    Intelligent System Design: Proceedings of Intelligent System Design: INDIA … , 2020
    2020
    Citations: 21
  • Minimization of Energy Consumption in Wireless Sensor Networks by Using a Special Mobile Agent
    SS , Padmalaya Nayak, Sujatha Dandu
    Soft Computing and Signal Processing 900, 359-368 , 2019
    2019
    Citations: 19
  • A Logical Design of Robust Methodology to Detect and Classify Melanoma Disease using Hybrid Deep Learning Principles
    K Priyadharshini, S Shanthi, R Ashwini, T Joel, TVV Satyanarayana
    2023 International Conference on Innovative Computing, Intelligent … , 2023
    2023
    Citations: 18
  • An automation query expansion strategy for information retrieval by using fuzzy based grasshopper optimization algorithm on medical datasets
    U Srivel, R., Kalaiselvi, K., Shanthi, S., Perumal
    Concurrency and Computation: Practice and Experience 35 (Issue3), 7418 , 2022
    2022
    Citations: 13
  • A secured and optimized deep recurrent neural network (DRNN) scheme for remote health monitoring system with edge computing
    D Pavithra, R Nidhya, S Shanthi, P Priya
    Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i … , 2023
    2023
    Citations: 11
  • Linear and Quadratic Radiation of Dynamical Non-Fourier Flux in a Disk Flow with the Suspension of Hybrid Nanoparticles
    S Suresh, SR Shanthi, AG Madaki, M Sathish Kumar, CSK Raju
    Journal of Nanofluids 12 (3), 786-795 , 2023
    2023
    Citations: 6
  • Biometric Authentication Techniques and Its Future
    shanthi sivakumar
    Biometric Authentication in Online Learning Environments, 122-148 , 2019
    2019
    Citations: 6
  • Analysis of COVID-19 Epidemic Disease Dynamics Using Deep Learning
    K Nirmala Devi, S Shanthi, K Hemanandhini, S Haritha, S Aarthy
    Proceedings of 7th International Conference on Harmony Search, Soft … , 2022
    2022
    Citations: 5
  • An Efficient IoT framework for patient monitoring and predicting heart disease based on machine learning algorithms
    S Shanthi, R Nidhya, U Perumal, M Kumar
    Tele‐Healthcare: Applications of Artificial Intelligence and Soft Computing … , 2022
    2022
    Citations: 4
  • A Fuzzy Logic based Dynamic Channel allocation Scheme for wireless Cellular networks to optimize the frequency reuse
    P Nayak, V Bhavani, M Shanthi
    IEEE Region 10 Conference (TENCON)— Proceedings of the International … , 2016
    2016
    Citations: 4
  • Automatic lung cancer detection and classification using Modified Golf Optimization with densenet classifier
    S Shanthi, JA Smitha, S Saradha
    International Journal of Information Technology 17 (3), 1551-1559 , 2025
    2025
    Citations: 3
  • Breast cancer detection using bimodal image fusion: Thermography and mammography images
    PB Prabira Kumar Sethy 1 , S. Shanthi2 , Komma Anitha 3 , A. Geetha Devi3
    Oncology and Radiotherapy 16 (6), 1-5 , 2022
    2022
    Citations: 3
  • Cellular automata and their realizations
    S Shanthi, PS Rao, MM Latha, EG Rajan
    2012 International Conference on Computing Sciences, 58-63 , 2012
    2012
    Citations: 3
  • Unravelling emotional well-being: detecting stress in social media through advanced deep learning techniques
    S Shanthi, P Kavya, P Kaviya, A Lokesh, K Nirmala Devi
    2025 International Conference on Emerging Smart Computing and Informatics … , 2025
    2025
    Citations: 2
  • Optimized Routing on Wireless Body Sensor Network Using Adaptive Lion Optimization Algorithm for IoT
    JA Smitha, S Shanthi, T Kumar, S Justin
    SSRG International Journal of Electrical and Electronics Engineering 9 (12 … , 2022
    2022
    Citations: 2
  • Recognition of botnet by examining link failures in cloud network by exhausting canfes classifier approach
    S Nagendra Prabhu, D Shanthi Saravanan, V Chandrasekar, S Shanthi
    Intelligent System Design: Proceedings of Intelligent System Design: INDIA … , 2020
    2020
    Citations: 2
  • “Hyperspectral image denoising based on self-similarity and bm3d
    VS V. V. Satyanarayana Tallapragada, S Shanti
    Journal of Advanced Research in Dynamical and Control Systems 9 (Sp– 17 … , 2018
    2018
    Citations: 2
  • Prevalence of tobacco usage in rural population in Tamil Nadu-A study
    AR Kumar, VR Malini, K Rajkumar, TD Kumar, G Nandhini, MA Kumar, ...
    SRM Journal of Research in Dental Sciences 2 (1), 15-19 , 2011
    2011
    Citations: 2