Dr. S. Saravanan

@veltech.edu.in

Assistant Professor (Sr.G) and Computer Science and Engineering
Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology,Chennai

Dr. S. Saravanan


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https://researchid.co/saravanansiddhan

EDUCATION

B.Tech., M.E., Ph.D

RESEARCH, TEACHING, or OTHER INTERESTS

, Computer Engineering
35

Scopus Publications

240

Scholar Citations

7

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Automatic screening of retinal lesions for detecting diabetic retinopathy using adaptive multiscale MobileNet with abnormality segmentation from public dataset
    Nandhini Selvaganapathy, Saravanan Siddhan, Parthasarathy Sundararajan, Sathiyaprasad Balasundaram
    Network Bristol England, 2026
    Owing to the epidemic growth of diabetes, ophthalmologists need to examine the huge fundus images for diagnosing the disease of Diabetic Retinopathy (DR). Without proper knowledge, people are too lethargic to detect the DR. Therefore, the early diagnosis system is requisite for treating ailments in the medical industry. Therefore, a novel deep model-based DR detection structure is recommended to fix the aforementioned difficulties. The developed deep model-based diabetic retinopathy detection process is performed adaptively. The DR detection process is imitated by garnering the images from benchmark sources. The gathered images are further preceded by the abnormality segmentation phase. Here, the Residual TransUNet with Enhanced loss function is used to employ the abnormality segmentation, and the loss function in this structure may be helpful to lessen the error in the segmentation procedure. Further, the segmented images are passed to the final phase of retinopathy detection. At this phase, the detection is carried out through the Adaptive Multiscale MobileNet. The variables in the AMMNet are optimized by the Adaptive Puzzle Optimization to obtain better detection performance. Finally, the effectiveness of the offered approach is confirmed by the experimentation procedure over various performance indices.
  • A Transfer Learning Framework for Multimodal Emotion Detection using Wav2Vec, EfficientNet, and LSTM
    M. Jagadeesh, N. Duraimurugan, Karthikeyan. U, Saravanan Siddhan
    Proceedings of 2nd International Conference on Visual Analytics and Data Visualization Icvadv 2026, 2026
    Human-computer interaction is based on emotion recognition, which allows the systems in artificial intelligence and robotics to react to users in a truly empathetic way. This paper proposes a powerful, multimodal system of recognizing a wide range of human emotions when communicating naturally. We optimize three state-of-the-art pre-trained audio, video, and text models based on Wav2Vec, EfficientNet, and LSTM respectively, to a fresh, annotated ad hoc collection of expressions of affect. Using a combination of the complementary cues of these modalities, our system is more accurate than any of the unimodal baselines, and the dataset itself is a useful resource in future affective computing research.
  • Milk Spoilage Analyser for Predicting Shelf Life Using Microbial Activity
    Ramkumar S, Mohan Raj S, Likhit S, Manishankar M, Naveensurya V, Saravanan S
    2026 2nd International Conference on Intelligent Systems for Communication Iot and Security Iciscois 2026, 2026
    India, the largest milk producer in the world with an annual production of approximately 239 million tonnes, suffers losses of almost 3-4 percent of milk (worth of over 25,000 crores annually) as a result of microbial contamination, poor cold-chain infrastructure and low quality of storage. This spoilage is not only bad to the economy but also it creates threats to the health of the population. Traditional milk quality measurement techniques involve use of sensory assessment and expiry dates labeling which is prone to inaccuracy and time wastage. This paper is a proposal of a Smart Milk Spoilage Analyzer that combines pH, temperature, gas, and turbidity sensors and an ESP32 microcontroller to monitor in real-time. A random forest regression model is used to process the data collected and classify the milk as being fresh, a warning, or spoiled and also predict the remaining shelf life of that milk. It was experimentally demonstrated that pH fell to 5.6 down to 6.7, turbidity rose to 1.6 NTU up to 0.2, and the model had a 96.8% classification accuracy having a 0.3-hour prediction error. The system is inexpensive (approximately 1200 rupees), mobile, and have Internet of Things (IoT) capabilities and thus suit rural and commercial dairy supply chains. It can help in early diagnosis of spoilage, minimize on wastage and increase food safety by means of remote, noninvasive monitoring.
  • A Multi-Stage Machine Learning Framework for Cyberattack Detection and Classification
    Latha R, Caleb S, Saravanan S
    2025 2nd Asia Pacific Conference on Innovation in Technology Apcit 2025, 2025
    Cyber-attacks become one of the problems that is larger and more complicated than it is now for the security and credibility of computer systems and networks. The Intrusion Detection Systems (IDS) play a fundamental role in signaling and mitigating these attacks, employing tools that monitor network traffic in order to catch behavior that proves to be anomalous. Here, in the framework is designed for detectives the cyber-attacks, by classifying cyber datasets for intrusion detection. In this framework, we use Machine Learning(ML) to process huge data flows of network signatures that are linked to the attacks from different groups. We use a multi-stage method in which data processing take place first, feature extraction is next, and model training with evaluation go hand in hand. Our performance is assessed using the top-ranking NSL-KDD or UNSW-NB15 datasets by means of popularly used intrusion detection methodology. The aim of our research is to confirm the provedness of the proposed anti-virus framework, which accurately detects different types of cyber-attacks including Denial of Service (DoS), Distributed Denial of Service (DDoS) and probing attacks. In addition to that we compare the operates of different learning methods and features selections to point out the most successful one for intrusion detection In all, the proposed structure constitutes a robust and scalable model that is fit for the purpose of launching attacks in real-time network protocols.
  • Enhancing Parental Monitoring of Tech-Savvy Children: A Comparison of Keylogger Software vs. Traditional Control Methods
    Latha. R, Caleb S, Saravanan S
    International Conference on Electrical Energy Systems Icees, 2025
    The digital world presents children to increased threats from their online actions such as exposure to unhealthy content, cyberbullying, and unethical behaviors such as hacking. The most common traditional forms of parental control, such as web filtering, time limitations on usage of devices, and app blocking, are commonly used to monitor and control children’s communication online. These efforts are often unfruitful, in particular, when kids with sophisticated technical capabilities can either bypass or turn off them off. This investigation assesses the function of keylogger software in helping to enhance parental control and assesses its usefulness compared to other parental control measures. The study aims to examine the use of keylogger software to provide children’s online behaviour with greater focus compared to what is achievable through conventional tools, for instance; tracking keystrokes, monitoring website activity, and observing communication habits. In the first step, baseline data is collected with the help of traditional parental controls, and the efficacy with which these tools can detect risky digital actions is assessed. To take a close look at the performance of keylogger programs, the second phase covers the attachment of keyloggers to devices of the participants for constant monitoring and intake of risks. We analyze the results provided by both methods during the third phase, but we pay a special attention to the rates of detections, speed of the interventions and the comparison of outcomes in the context of the parental responses. According to the study, keyloggers perform better than traditional methods in detecting dangerous practices namely detection of inappropriate content, cyberbullying and unethical actions. Our implementation of keyloggers leads to timely interventions as well as the more efficient reactions from parents to the online risks. While providing more extensive monitoring, a key of a keyloggers’ comprehensive nature leads to the emergence of privacy issues. However, parents were more content with keyloggers, as they succeeded in providing protection online to children. The research suggests this tool might create a safer and more responsible way for parental overseeing.
  • Sustainable agriculture through big data analytics: The role of ABC-RLS algorithm in enhancing crop production
    K. Vijaya Bhaskar, R. Gnana Jeyaraman, S. Saravanan, S. Nandhini
    Environment Development and Sustainability, 2025
  • Synergizing AI, IoT, and Cyber-Physical Systems: A Cross-Domain Approach for Smart Infrastructure, Secure Networks, and Sustainable Intelligence
    M. Suresh, M Jayaprakash, Saju Raj T, Geetha Ponnaian, Moorthy Agoramoorthy, Saravanan Siddhan
    2025 2nd International Conference on Computing and Data Science Iccds 2025, 2025
    Modern infrastructure development undergoes a disruptive change because of the technological unification between Artificial Intelligence (AI) and Internet of Things (IoT) and Cyber-Physical Systems (CPS). The technical connection brings about independent choice functions along with distributed management abilities and improved system responsiveness in real-time. The framework demonstrates 26.3% energy savings, 93-96% attack detection accuracy, and 38% latency reduction compared to traditional systems through blockchain-secured federated learning. Obj ect integration generates challenges with these domains concerning data reliability and system durability along with interoperability issues. A unified framework that integrates data analytics and distributed sensing with real-time cyber-physical systems interaction represents the proposed solution to handle these problems. The system structure uses edge computing to cut down latency while managing data privacy with federated learning along with decentralized control capabilities for adaptive system function. The application of blockchain security creates dependable message exchange along with preventive cyber defense capabilities. The tested framework demonstrated its ability to enhance speed of processing together with energy savings and anomaly recognition capabilities in a smart campus simulation environment. Testing results have demonstrated that implementing AI along with IoT and CPS results in the development of resilient and large-scale smart infrastructure technology with sustain ability features.
  • Real-Time Human Intrusion Detection in Wireless Sensor Networks Using Yolov7 for Enhanced Perimeter Security
    Thinakaran K, Saravanan Siddhan, Kalisetti Purushotham Prasad, Y V Reddy, Mohan R, Aanjey Mani Tripathi
    2025 3rd International Conference on Communication Security and Artificial Intelligence Iccsai 2025, 2025
    Real time human intrusion detection is another essential part of today's perimeter security, especially for constrained systems such as WSNs. Based on the obtained results, this paper suggests the implementation of a human intrusion detection system with YOLOv7 due to its improved detection performance, power consumption, and real-time performance. The system takes advantage of YOLOv7 for enhanced feature extraction and detection thereby having precision of 94.3 %, recall of 92.8 % and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F 1$</tex>-score of 93.5. In this work, the authors also propose integrating with WSNs to save energy by 16.4 % compared to similar systems using YOLOv5. A high probability of detecting the movement of objects is achieved, and strong performance is possible at various environmental conditions. The system also increases the alert effectiveness with faster detection to alert time of 90 ms and fewer false & missed detections. These advancements make the proposed approach feasible and efficient for the intended applied real-time perimeter security solution which would be responsive to some of the current unconventional intrusion situations.
  • Federated Learning Using Blockchain for Decentralized and Enhanced secure network management driven by Artificial Intelligence
    Mohammed H. F, Sasi Bhanu, S. Janarthanan, S. Alagumuthukrishnan, Gurram Vijendar Reddy, Saravanan Siddhan
    2025 International Conference on Computational Innovations and Engineering Sustainability Iccies 2025, 2025
    6G network management is enabled by a secure and decentralized framework that integrates Federated Learning (FL) with Blockchain technology. This framework enhances AI-based decision-making and ensures data privacy. Without relying on centralized data aggregation, this integration ensures intelligence diffusion among edge devices is seamless. Due to their dependence on centralized training of AI models and outdated cloud-based infrastructures, existing solutions suffer from privacy concerns, high latency, and security vulnerabilities. These limitations make it more difficult to dynamically optimize networks and securely transfer data in large-scale, dynamic 6G environments. To ensure decentralized model training of AI and utilize Blockchain for secure and irreversible transactions, the proposed system combines Smart Contracts with a Federated Learning Consensus Mechanism (SC-FLCM). The consensus mechanism ensures model updates without revealing raw data, makes safe data-sharing agreements automatic, and smart contracts enhance efficiency and security. 6G smart Internet of Things (IoT) services, real-time resource allocation, and secure network slicing are all great examples for the proposed method. Strong security, trust, and adaptive learning are assured over various network architectures. The system outperforms traditional cloud-based AI methodologies significantly when evaluated against them in terms of data privacy (98.7% increase), latency optimization (42.5%), and accuracy of AI models (96.2%).
  • IoT-based trusted wireless communication framework by machine learning approach
    S. Chakaravarthi, S. Saravanan, M. Jagadeesh, S. Nandhini
    Measurement Sensors, 2024
    The traditional Radio-Frequency Systems (RFS) authentication methods, designed to ensure secure data transmission on the web, may not always effectively prevent adversaries from gaining access to concealed IDs or asymmetric cryptography through infiltrative, side-channel, training, and computer attacks. In contrast, Unaccounted Information (UAI) has the potential to exploit irregularities in production systems to automatically identify microchips, offering a highly robust and cost-effective security solution. This approach introduces RFS-UAI, a deep neural network-based system that efficiently manages wireless node identification by leveraging synthetic RFS characteristics of remote controls (Tx) learned through supervised methods in Wireless Sensor Networks (WSN). Unlike traditional methods that require the development of specialized transistors for UAI or semantic segmentation, this approach utilizes the existing asymmetrical RFS communication networks. Similar to the way the human brain processes information, Rx handles the entire device identification process at the gateway. According to test results, which include assessing process capability at a specified 65 nm threshold voltage and characteristics such as Local Oscillator (LO) misalignment and I-Q disparity using a probabilistic model with 52 hidden units, the system can distinguish up to 4800 transmitters with a remarkable 99.9 % accuracy under various channel conditions, all without the need for regular preambles. This recommended method can serve as a standalone security measure or be integrated into a biometric identification system.
  • Simplified Image Encryption Algorithm (SIEA) to enhance image security in cloud storage
    M. Lavanya, K. Joseph Abraham Sundar, S. Saravanan
    Multimedia Tools and Applications, 2024
  • An efficient optimal hybrid SVELM based monitoring and forecasting the engine operations for safety standards
    S. Nandhini, S. Parthasarathy, S. Saravanan
    Expert Systems with Applications, 2024
  • Health Analysis and Prediction Using Machine Learning
    B. Renukadevi, K.S. Velmurugan, S. Saravanan
    2024 International Conference on Communication Computing and Internet of Things Ic3iot 2024 Proceedings, 2024
  • Applying Computational Topology for Enhanced Image Recognition and Computer Vision
    Saravanan Siddhan, A. Moorthy, S. Christy, C. Sivasankar, K. Vijaya Bhaskar
    2nd IEEE International Conference on Advances in Information Technology Icait 2024 Proceedings, 2024
  • Java-Powered Digital Healthcare Management: innovating Medical Administration Systems
    M. Kathiravan, I. Lakshmi, V. Sathya Durga, S. Saravanan, M. Vijayakumar, N. Bharathiraja
    Proceedings International Conference on Computing Power and Communication Technologies Ic2pct 2024, 2024
  • A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography
    I. Sudha, Cecil Donald, S. Navya, G. Nithya, Manivannan Balamurugan, S. Saravanan
    Proceedings of the 2nd International Conference on Intelligent and Innovative Technologies in Computing Electrical and Electronics Iciitcee 2024, 2024
  • Deep Learning-Driven Sentiment Analysis in Textual Data
    M. Kathiravan, S. Saravanan, M Jagadeesh, I. Lakshmi, V Sathya Durga, N. Bharathiraja
    Proceedings International Conference on Computing Power and Communication Technologies Ic2pct 2024, 2024
  • Weather Prediction(analysis) using Soft kind of Computing techniques
    Pogiri Revathi, Santhoshi Bhavani, G Karthika Priya Dharshini, Gnanajeyaraman Rajaram, Saravanan Siddhan, Rajat Kumar Dwibedi
    2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2024, 2024
  • Big Data analytics for privacy through ND-homomorphic encryption
    S. Saravanan, N. Poornima
    Journal of Control and Decision, 2023
  • Sustainable Algorithms using Artificial Intelligence and Various Stages for Precision Agricultural Cultivation
    Kalaiselvi V.K.G, Jagadeesh Gopalakrishnan, Sahana Shri Anand, Shanmugasundaram Hariharan, Sivasankaran Saravanan, Hemalatha Annamalai
    Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2023, 2023
  • Cybersecurity Audits for Emerging and Existing Cutting Edge Technologies
    Sivasankaran Saravanan, Anup Menon, Kavya Saravanan, Shanmugasundaram Hariharan, Leema Nelson, Jegadeesh Gopalakrishnan
    Ised 2023 International Conference on Intelligent Systems and Embedded Design, 2023
  • Copyright Protection Algorithm of Digital and Artistic Products based on Fuzzy Clustering
    M. Rajasekar, K. Sambath Kumar, S. Saravanan, Pradeep Kumar, M. Sridharan, Saveetha R
    2023 2nd International Conference on Smart Technologies for Smart Nation Smarttechcon 2023, 2023
  • Research on Optimization Algorithm of Real Estate Enterprise Value Evaluation Based on BP Neural Network
    Niranjanamurthy M, S. Surendran, S. Saravanan, Tulsidas Nakrani, Mahaveerakannan R, M. R. Arun
    2023 2nd International Conference on Smart Technologies for Smart Nation Smarttechcon 2023, 2023
  • Artificial Intelligence Security Model For Privacy Renitence In Big Data Analytics
    Applied Mathematics and Information Sciences, 2022
  • COVID-19 Related Lung Disease Detection and Classification USING a Deep Learning System
    S. Saravanan, V. Prithviraju, A. Alli Rani
    2022 1st International Conference on Computational Science and Technology Iccst 2022 Proceedings, 2022
  • Farming Using AI Technology
    N Shivaanivarsha, A G Vijayendiran, S Saravanan, A Sriram
    2022 IEEE International Power and Renewable Energy Conference Iprecon 2022, 2022
  • Intelligent Deep Residual Network based Brain Tumor Detection and Classification
    K. Kartheeban, Kapula Kalyani, Sai Krishna Bommavaram, Divya Rohatgi, Mathur Nadarajan Kathiravan, S. Saravanan
    International Conference on Automation Computing and Renewable Systems Icacrs 2022 Proceedings, 2022
  • Artificial Intelligence Influence on Accounting Methods
    Somanchi Hari Krishna, Manjula Pattnaik, Anand Patil, Kamarajugadda Tulasi Vigneswara Rao, Iskandar Muda, S. Saravanan
    Proceedings of 5th International Conference on Contemporary Computing and Informatics Ic3i 2022, 2022
  • Securing Biometric Data with Optimized Share Creation and Visual Cryptography Technique
    Shammi L, Milind, C. Emilin Shyni, Khair Ul Nisa, Ravi Kumar Bora, S. Saravanan
    6th International Conference on Electronics Communication and Aerospace Technology Iceca 2022 Proceedings, 2022
  • A hybrid chaotic map with coefficient improved whale optimization-based parameter tuning for enhanced image encryption
    S. Saravanan, M. Sivabalakrishnan
    Soft Computing, 2021
  • High-Frequency Noise Removal on Corrupted ECG Signal Using Exponential Averagers
    R. Mohan Raj, P. Thanapal, S. Saravanan, M. Sundar Prakash Balaji, V. Elamaran
    Communications in Computer and Information Science, 2021
  • Baseline Wandering Noise Removal Using High-Speed IIR Filters with an FPGA Implementation
    R. Mohan Raj, Vemula Rajesh, S. Saravanan, M. Sundar Prakash Balaji, V. Elamaran
    Communications in Computer and Information Science, 2021
  • Optimal Image Encryption in Frequency Domain using Hybrid Deer Hunting with Artificial Bee Colony with Hybrid Chaotic Map
    Applied Mathematics and Information Sciences, 2020
  • Electroencephalogram based communication system for locked in state person using mentally spelled tasks with optimized network model
    Xu Xiaoxiao, Luo Bin, S. Ramkumar, S. Saravanan, M. Sundar Prakash Balaji, S. Dhanasekaran, J. Thimmiaraja
    Artificial Intelligence in Medicine, 2020
  • Entropy analysis for achieving high compression ratio
    Journal of Theoretical and Applied Information Technology, 2011

RECENT SCHOLAR PUBLICATIONS

  • Automatic screening of retinal lesions for detecting diabetic retinopathy using adaptive multiscale MobileNet with abnormality segmentation from public dataset
    N Selvaganapathy, S Siddhan, P Sundararajan, S Balasundaram
    Network: Computation in Neural Systems 37 (1), 1-33 , 2026
    2026
    Citations: 2
  • Sustainable agriculture through big data analytics: The role of ABC-RLS algorithm in enhancing crop production: KV Bhaskar et al.
    KV Bhaskar, RG Jeyaraman, S Saravanan, S Nandhini
    Environment, Development and Sustainability, 1-25 , 2025
    2025
    Citations: 1
  • Real-time human intrusion detection in wireless sensor networks using YOLOv7 for enhanced perimeter security
    K Thinakaran, S Siddhan, KP Prasad, YV Reddy, R Mohan, AM Tripathi
    2025 3rd International Conference on Communication, Security, and Artificial … , 2025
    2025
    Citations: 1
  • IoT-based trusted wireless communication framework by machine learning approach
    S Chakaravarthi, S Saravanan, M Jagadeesh, S Nandhini
    Measurement: Sensors 34, 101271 , 2024
    2024
    Citations: 3
  • Applying Computational Topology for Enhanced Image Recognition and Computer Vision
    S Siddhan, A Moorthy, S Christy, C Sivasankar, KV Bhaskar
    2024 Second International Conference on Advances in Information Technology … , 2024
    2024
  • Weather Prediction (analysis) using Soft kind of Computing techniques
    P Revathi, S Bhavani, GKP Dharshini, G Rajaram, S Siddhan, ...
    2024 4th International Conference on Advance Computing and Innovative … , 2024
    2024
    Citations: 5
  • An efficient optimal hybrid SVELM based monitoring and forecasting the engine operations for safety standards
    S Nandhini, S Parthasarathy, S Saravanan
    Expert Systems with Applications 238, 121679 , 2024
    2024
    Citations: 3
  • Deep Learning-Driven Sentiment Analysis in Textual Data
    M Kathiravan, S Saravanan, M Jagadeesh, I Lakshmi, VS Durga, ...
    2024 IEEE International Conference on Computing, Power and Communication … , 2024
    2024
    Citations: 2
  • Java-Powered Digital Healthcare Management: innovating Medical Administration Systems
    M Kathiravan, I Lakshmi, VS Durga, S Saravanan, M Vijayakumar, ...
    2024 IEEE International Conference on Computing, Power and Communication … , 2024
    2024
    Citations: 4
  • A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography
    I Sudha, C Donald, S Navya, G Nithya, M Balamurugan, S Saravanan
    2024 International Conference on Intelligent and Innovative Technologies in … , 2024
    2024
    Citations: 22
  • Copyright Protection Algorithm of Digital and Artistic Products based on Fuzzy Clustering
    M Rajasekar, KS Kumar, S Saravanan, P Kumar, M Sridharan
    2023 Second International Conference On Smart Technologies For Smart Nation … , 2023
    2023
    Citations: 1
  • Research on Optimization Algorithm of Real Estate Enterprise Value Evaluation Based on BP Neural Network
    M Niranjanamurthy, S Surendran, S Saravanan, T Nakrani, ...
    2023 Second International Conference On Smart Technologies For Smart Nation … , 2023
    2023
  • Big Data analytics for privacy through ND-homomorphic encryption
    S Saravanan, N Poornima
    Journal of Control and Decision 10 (1), 64-71 , 2023
    2023
    Citations: 3
  • Dim Recognition in Images, Videos and Real-Time Video Streams
    M Kathiravan, RG Sakthivelan, S Saravanan, SG Hari Hara Sudhan, ...
    Sentiment Analysis and Deep Learning: Proceedings of ICSADL 2022, 703-715 , 2023
    2023
  • Artificial Intelligence Security Model For Privacy Renitence In Big Data Analytics
    D Saravanan, S., Sivabalakrishnan, M., Duraimurugan, N., Divya
    Applied Mathematics and Information Sciences 16 (6), pp. 919–927 , 2023
    2023
    Citations: 24
  • Intelligent Deep Residual Network based Brain Tumor Detection and Classification
    K Kartheeban, K Kalyani, SK Bommavaram, D Rohatgi, MN Kathiravan, ...
    2022 International Conference on Automation, Computing and Renewable Systems … , 2022
    2022
    Citations: 8
  • A hybrid chaotic map with coefficient improved whale optimization-based parameter tuning for enhanced image encryption: S. Saravanan, M. Sivabalakrishnan
    S Saravanan, M Sivabalakrishnan
    Soft Computing 25 (7), 5299-5322 , 2021
    2021
    Citations: 51
  • Optimal Image Encryption in Frequency Domain using Hybrid Deer Hunting with Artificial Bee Colony with Hybrid Chaotic Map
    SS M Sivabalakrishnan
    International Journal of Applied Mathematics & Information Sciences 14 (6 … , 2020
    2020
    Citations: 4
  • An image encryption scheme using chaotic baker map
    S Saravanan, M Sivabalakrishnan
    Journal of Computational and Theoretical Nanoscience 17 (5), 2130-2135 , 2020
    2020
    Citations: 2
  • A Framework for Digital Image Encryption using Chaotic Baker Map with SHA Algorithm
    SS M Sivabalakrishnan
    International Journal of Innovative Technology and Exploring Engineering … , 2019
    2019

MOST CITED SCHOLAR PUBLICATIONS

  • Partition of tannery wastewater proteins in aqueous two-phase poly (ethylene glycol)-magnesium sulfate systems: effects of molecular weights and pH
    S Saravanan, JR Rao, T Murugesan, BU Nair, T Ramasami
    Chemical engineering science 62 (4), 969-978 , 2007
    2007
    Citations: 62
  • A hybrid chaotic map with coefficient improved whale optimization-based parameter tuning for enhanced image encryption: S. Saravanan, M. Sivabalakrishnan
    S Saravanan, M Sivabalakrishnan
    Soft Computing 25 (7), 5299-5322 , 2021
    2021
    Citations: 51
  • Quantification of total phenolic content, HPLC analysis of flavonoids and assessment of antioxidant and anti-haemolytic activities of Hibiscus rosa-sinensis L. flowers in vitro
    A Purushothaman, P Meenatchi, S Saravanan, R Sundaram, ...
    Int J Pharma Res Health Sci 4 (5), 1342-1350 , 2016
    2016
    Citations: 25
  • Artificial Intelligence Security Model For Privacy Renitence In Big Data Analytics
    D Saravanan, S., Sivabalakrishnan, M., Duraimurugan, N., Divya
    Applied Mathematics and Information Sciences 16 (6), pp. 919–927 , 2023
    2023
    Citations: 24
  • A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography
    I Sudha, C Donald, S Navya, G Nithya, M Balamurugan, S Saravanan
    2024 International Conference on Intelligent and Innovative Technologies in … , 2024
    2024
    Citations: 22
  • Dynamic Voltage Restorer for Distribution System
    S Saravanan, M Solaimanigandan, T Tharaneetharan, V Varunraj, ...
    International Journal of Engineering Research and Development e-ISSN 2278, 14-24 , 2013
    2013
    Citations: 14
  • Intelligent Deep Residual Network based Brain Tumor Detection and Classification
    K Kartheeban, K Kalyani, SK Bommavaram, D Rohatgi, MN Kathiravan, ...
    2022 International Conference on Automation, Computing and Renewable Systems … , 2022
    2022
    Citations: 8
  • Weather Prediction (analysis) using Soft kind of Computing techniques
    P Revathi, S Bhavani, GKP Dharshini, G Rajaram, S Siddhan, ...
    2024 4th International Conference on Advance Computing and Innovative … , 2024
    2024
    Citations: 5
  • Java-Powered Digital Healthcare Management: innovating Medical Administration Systems
    M Kathiravan, I Lakshmi, VS Durga, S Saravanan, M Vijayakumar, ...
    2024 IEEE International Conference on Computing, Power and Communication … , 2024
    2024
    Citations: 4
  • Optimal Image Encryption in Frequency Domain using Hybrid Deer Hunting with Artificial Bee Colony with Hybrid Chaotic Map
    SS M Sivabalakrishnan
    International Journal of Applied Mathematics & Information Sciences 14 (6 … , 2020
    2020
    Citations: 4
  • IoT-based trusted wireless communication framework by machine learning approach
    S Chakaravarthi, S Saravanan, M Jagadeesh, S Nandhini
    Measurement: Sensors 34, 101271 , 2024
    2024
    Citations: 3
  • An efficient optimal hybrid SVELM based monitoring and forecasting the engine operations for safety standards
    S Nandhini, S Parthasarathy, S Saravanan
    Expert Systems with Applications 238, 121679 , 2024
    2024
    Citations: 3
  • Big Data analytics for privacy through ND-homomorphic encryption
    S Saravanan, N Poornima
    Journal of Control and Decision 10 (1), 64-71 , 2023
    2023
    Citations: 3
  • Automatic screening of retinal lesions for detecting diabetic retinopathy using adaptive multiscale MobileNet with abnormality segmentation from public dataset
    N Selvaganapathy, S Siddhan, P Sundararajan, S Balasundaram
    Network: Computation in Neural Systems 37 (1), 1-33 , 2026
    2026
    Citations: 2
  • Deep Learning-Driven Sentiment Analysis in Textual Data
    M Kathiravan, S Saravanan, M Jagadeesh, I Lakshmi, VS Durga, ...
    2024 IEEE International Conference on Computing, Power and Communication … , 2024
    2024
    Citations: 2
  • An image encryption scheme using chaotic baker map
    S Saravanan, M Sivabalakrishnan
    Journal of Computational and Theoretical Nanoscience 17 (5), 2130-2135 , 2020
    2020
    Citations: 2
  • A framework for digital image encryption using chaotic baker map with SHA algorithm [J]
    S Saravanan, M Sivabalakrishnan
    International Journal of Innovative Technology and Exploring Engineering 2 … , 2019
    2019
    Citations: 2
  • Sustainable agriculture through big data analytics: The role of ABC-RLS algorithm in enhancing crop production: KV Bhaskar et al.
    KV Bhaskar, RG Jeyaraman, S Saravanan, S Nandhini
    Environment, Development and Sustainability, 1-25 , 2025
    2025
    Citations: 1
  • Real-time human intrusion detection in wireless sensor networks using YOLOv7 for enhanced perimeter security
    K Thinakaran, S Siddhan, KP Prasad, YV Reddy, R Mohan, AM Tripathi
    2025 3rd International Conference on Communication, Security, and Artificial … , 2025
    2025
    Citations: 1
  • Copyright Protection Algorithm of Digital and Artistic Products based on Fuzzy Clustering
    M Rajasekar, KS Kumar, S Saravanan, P Kumar, M Sridharan
    2023 Second International Conference On Smart Technologies For Smart Nation … , 2023
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