BHARATH KUMARA

@msruas.ac.in

Assistant Professor, ECE
M S Ramaiah University of Applied Science

BHARATH KUMARA


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https://researchid.co/bharathkumara

EDUCATION

BE, M.Tech,. Ph.D

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Computer Networks and Communications, Computer Science, Electronic, Optical and Magnetic Materials
10

Scopus Publications

35

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Supervised Machine Learning Evaluation for Patient-Specific and Non-Patient-Specific Epileptic Seizure Detection with Multichannel Scalp EEG
    Vijay C. P., Mahendra G., Bharath K. N., Suhaas K. P., Bharath Kumara, et al.
    SN Computer Science, 2025
  • Machine Learning and Deep Learning Approaches for Guava Disease Detection
    K. Paramesha, Shruti Jalapur, Shalini Hanok, Kiran Puttegowda, G. Manjunatha, et al.
    SN Computer Science, 2025
  • Optimized Machine Learning Techniques for Precise Breast Cancer Detection in Mammograms
    Puttegowda Kiran, V. Veeraprathap, U. Rajashekhar, Mathapati Mahantesh, K. V. Sudheesh, et al.
    SN Computer Science, 2025
  • Assessment of Autism Spectrum Disorder in Toddlers Using Speech Features and SVM Model
    Soumya G V, Purnima P S, Neethi M V, Yuvaraja B K, Kiran Puttegowda, et al.
    3rd IEEE International Conference on Networks Multimedia and Information Technology Nmitcon 2025, 2025
  • Music Instruments Classification Using Signal Processing and Machine Learning
    Harshith Chandrashekar, Swetha K T, Ambika V, Kiran Puttegowda, Bharath Kumara, et al.
    3rd IEEE International Conference on Networks Multimedia and Information Technology Nmitcon 2025, 2025
  • Enhancing Speech Quality Using Mask-Based CNN and GAN Architectures
    Soumya G V, Lekhashree M K, Jyothi H, Thejaswini R, Ashwini P, et al.
    International Conference on Emerging Technologies in Electronics and Green Energy Iceteg 2025, 2025
  • AI-Enhanced Virtual Twin Modelling for Strengthening IoT Software Security Protocols
    Bharath Kumara, Pareshwar Prasad Barmola, Renuka Arora, Swapnil M Parikh, Ramya Maranan
    2024 1st International Conference on Software Systems and Information Technology Ssitcon 2024, 2024
    To fortify security mechanisms in software systems for the Internet of Things (IoT), this article presents a framework for AI-Enhanced Virtual Twin Modelling. In order to track and examine the actions of IoT devices in real-time, the suggested method makes use of virtual twin technology that is combined with machine learning techniques. Automated response generation, continuous threat assessment, and anomaly detection are made possible by creating a digital clone of the actual IoT network using the virtual twin paradigm. By combining deep learning models like CNNs and LSTMs, it becomes easier to forecast possible security risks in network traffic data by seeing intricate spatial and temporal patterns. When tested in a virtual Internet of Things (IoT) setting, the suggested framework outperforms conventional rule-based approaches by a wide margin, reducing reaction time by 35% while achieving an accuracy of $\\mathbf{9 6 . 2 \\%}$ in threat identification.
  • Secure Key Management in 5G Networks Using Elliptic Curve Integrated Encryption Scheme (ECIES) for Low-Power IoT Devices
    N Chitra Kiran., Meenakshi Maindola, Bharath Kumara, S. Kaliappan, Pooja Bhatt, et al.
    4th IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2024, 2024
    The rapid proliferation of the Internet of Things (IoT) has led to a surge in cyber threats, demanding the development of robust security frameworks. This paper introduces an advanced threat detection model, leveraging Artificial Intelligence (AI) and Cyber Twin Technologies for enhanced IoT security. The proposed framework integrates a Cyber Twin-a digital replica of physical IoT devices-with real-time data analytics to detect, predict, and respond to sophisticated cyber-attacks. The Cyber Twin continuously monitors IoT networks, identifying abnormal behaviors and enabling the implementation of dynamic security measures through AI-driven intrusion detection systems (IDS). A hybrid deep learning approach combining Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) is utilized to enhance anomaly detection and threat classification accuracy. The system's ability to simulate various attack scenarios within a digital environment facilitates the development of effective countermeasures while minimizing the impact on actual IoT operations. Experimental results demonstrate significant improvements in detection accuracy, reduced false positives, and enhanced system resilience. The proposed AI and Cyber Twin-based threat detection model sets a new benchmark in safeguarding IoT infrastructures against emerging cyber threats.
  • Multiple Chaotic Map based Selective Image Encryption Scheme for Medical Images
    Prabhavathi K, Maniunatha G, Savitha Shetty, Shilpa R, Kiran Puttegowda, et al.
    2nd IEEE International Conference on Integrated Intelligence and Communication Systems Iciics 2024, 2024
    Securing medical images is essential to protect patient privacy, particularly with the rise of telemedicine and eHealth/mHealth services, necessitating rapid and effective security measures. However, research on securing medical images with minimal processing time remains limited. This paper presents a selective encryption approach aimed at reducing processing time while ensuring robust security. In the developed scheme of the present study, a selective image security system, using multiple chaotic maps has been incorporated. The Region of Interest is selected either manually or a histogram based global threshold is used. The selected region is then subjected to a 2D logistic map and then XORed with the pseudo random series generated by a 3D Lorentz map. The applying of the diffused image over the input image gives a selectively encrypted image. The proposed novel image encryption scheme in this paper combines both logistic and Lorenz maps to improve the encryption capacity. Our experimental results demonstrate that the proposed method enhances the security performance more effectively than other methods in terms of entropy and correlation coefficients. The adopted encryption strategy also reveals high reliability against the brute force attacks with low processing delay required achieving high entropy and nearly zero correlation coefficients making it appropriate for real-time medical image applications.
  • Optimized data collection and computation using internet of things (IoT)
    Mr.Bharath Kumara, Dr. S. Anantha Padmanabhan, and
    International Journal of Innovative Technology and Exploring Engineering, 2019
    IOT is one of the standard data transfer technique used in day today applications like health monitoring, industrial data collection and in home security system. Security in data transmission is one of the major concerned research area in IOT. The existing methodologies is secure data transmission is not provided full fledge privacy for data collection and transmission. Hence, this paper proposed a new methodology to compute and secure the valuable data. The methodology to optimize the data collection is achieved in two different steps. The noise is added to original data in the first step to secure the original data. In second step different nodes in the network/clustered average data will be computed. Later the research methods is implementing to minimize the data loss. To show the performance of the optimal data collection and secure transmission we simulate different constraints of the network parameters and compared with existing methods. The developed algorithm proved that it is one of the better data collection technique.

RECENT SCHOLAR PUBLICATIONS

  • Early detection of skin diseases using deep learning approaches
    KV Sudheesh, B Kumara, K Puttegowda, RJ Kavitha, S Manasa, BN Divya, ...
    Information and Communication Systems, 126-132 , 2026
    2026.0
  • Enhancing Speech Quality Using Mask-Based CNN and GAN Architectures
    GV Soumya, MK Lekhashree, H Jyothi, R Thejaswini, P Ashwini
    2025 International Conference on Emerging Technologies in Electronics and … , 2025
    2025.0
  • Assessment of Autism Spectrum Disorder in Toddlers Using Speech Features and SVM Model
    GV Soumya, PS Purnima, MV Neethi, BK Yuvaraja, AC Ramachandra
    2025 Third International Conference on Networks, Multimedia and Information … , 2025
    2025.0
  • Music Instruments Classification Using Signal Processing and Machine Learning
    H Chandrashekar, KT Swetha, V Ambika, K Puttegowda, B Kumara, ...
    2025 Third International Conference on Networks, Multimedia and Information … , 2025
    2025.0
    Citations: 1
  • Supervised Machine Learning Evaluation for Patient-Specific and Non-Patient-Specific Epileptic Seizure Detection with Multichannel Scalp EEG
    V CP, M G, B KN, S KP, B Kumara, D RH, S KV
    SN Computer Science 6 (6), 680 , 2025
    2025.0
    Citations: 2
  • Optimized machine learning techniques for precise breast cancer detection in mammograms
    P Kiran, V Veeraprathap, U Rajashekhar, M Mahantesh, KV Sudheesh, ...
    SN Computer Science 6 (4), 384 , 2025
    2025.0
    Citations: 4
  • Machine learning and deep learning approaches for guava disease detection
    K Paramesha, S Jalapur, S Hanok, K Puttegowda, G Manjunatha, ...
    SN Computer Science 6 (4), 361 , 2025
    2025.0
    Citations: 23
  • Secure Key Management in 5G Networks Using Elliptic Curve Integrated Encryption Scheme (ECIES) for Low-Power IoT Devices
    NC Kiran, M Maindola, B Kumara, S Kaliappan, P Bhatt, R Maranan
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024.0
  • Multiple chaotic map based selective image encryption scheme for medical images
    K Prabhavathi, G Maniunatha, R Shilpa
    2024 International Conference on Integrated Intelligence and Communication … , 2024
    2024.0
    Citations: 1
  • AI-Enhanced Virtual Twin Modelling for Strengthening IoT Software Security Protocols
    B Kumara, PP Barmola, R Arora, SM Parikh, R Maranan
    2024 First International Conference on Software, Systems and Information … , 2024
    2024.0
  • A condition-based distributed approach for secured privacy preservation of nodes in wireless sensor networks IoT
    B Kumara, SA Padmanabhan
    International Journal of Reconfigurable and Embedded Systems 13 (2), 441-449 , 2024
    2024.0
    Citations: 4
  • Provable, Reliable And Secure Data Aggregation Through Integrated Distributed Mechanism In Iot Based WSN Environment
    MB Kumara
    Webology 18 (6), 1657-1676 , 2021
    2021.0
  • Optimized Data Collection and Computation using Internet of Things (IoT)
    SAP Bharath Kumara
    https://www.ijitee.org/wp-content/uploads/papers/v8i10/J90470881019.pdf 8 … , 2019
    2019.0
  • 1 GHz Inverse Filters using Operational Amplifier
    B Kumara, P Goel, P Sharma
    2019.0
  • Performance analysis of 1.6 Tbps Optical Code Division Multiple Access system using Multi-Diagonal Code
    B Kumara, R Deelip
    2019.0
  • Smart home security system with fire emergency response
    B Kumara, J Kishan, PS Patil, R Shivani, D Monicapriya
    2019.0
  • Street Lamp Control through an Infrared Sensor
    SK Nayak, B Kumara
    SASTech-Technical Journal of RUAS 17 (2), 17-20 , 2018
    2018.0
  • An Overview on operational amplifier as Multivibrator
    RJ Bose, P Bikramjeet, B Kumara

MOST CITED SCHOLAR PUBLICATIONS

  • Machine learning and deep learning approaches for guava disease detection
    K Paramesha, S Jalapur, S Hanok, K Puttegowda, G Manjunatha, ...
    SN Computer Science 6 (4), 361 , 2025
    2025.0
    Citations: 23
  • Optimized machine learning techniques for precise breast cancer detection in mammograms
    P Kiran, V Veeraprathap, U Rajashekhar, M Mahantesh, KV Sudheesh, ...
    SN Computer Science 6 (4), 384 , 2025
    2025.0
    Citations: 4
  • A condition-based distributed approach for secured privacy preservation of nodes in wireless sensor networks IoT
    B Kumara, SA Padmanabhan
    International Journal of Reconfigurable and Embedded Systems 13 (2), 441-449 , 2024
    2024.0
    Citations: 4
  • Supervised Machine Learning Evaluation for Patient-Specific and Non-Patient-Specific Epileptic Seizure Detection with Multichannel Scalp EEG
    V CP, M G, B KN, S KP, B Kumara, D RH, S KV
    SN Computer Science 6 (6), 680 , 2025
    2025.0
    Citations: 2
  • Music Instruments Classification Using Signal Processing and Machine Learning
    H Chandrashekar, KT Swetha, V Ambika, K Puttegowda, B Kumara, ...
    2025 Third International Conference on Networks, Multimedia and Information … , 2025
    2025.0
    Citations: 1
  • Multiple chaotic map based selective image encryption scheme for medical images
    K Prabhavathi, G Maniunatha, R Shilpa
    2024 International Conference on Integrated Intelligence and Communication … , 2024
    2024.0
    Citations: 1
  • Early detection of skin diseases using deep learning approaches
    KV Sudheesh, B Kumara, K Puttegowda, RJ Kavitha, S Manasa, BN Divya, ...
    Information and Communication Systems, 126-132 , 2026
    2026.0
  • Enhancing Speech Quality Using Mask-Based CNN and GAN Architectures
    GV Soumya, MK Lekhashree, H Jyothi, R Thejaswini, P Ashwini
    2025 International Conference on Emerging Technologies in Electronics and … , 2025
    2025.0
  • Assessment of Autism Spectrum Disorder in Toddlers Using Speech Features and SVM Model
    GV Soumya, PS Purnima, MV Neethi, BK Yuvaraja, AC Ramachandra
    2025 Third International Conference on Networks, Multimedia and Information … , 2025
    2025.0
  • Secure Key Management in 5G Networks Using Elliptic Curve Integrated Encryption Scheme (ECIES) for Low-Power IoT Devices
    NC Kiran, M Maindola, B Kumara, S Kaliappan, P Bhatt, R Maranan
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024.0
  • AI-Enhanced Virtual Twin Modelling for Strengthening IoT Software Security Protocols
    B Kumara, PP Barmola, R Arora, SM Parikh, R Maranan
    2024 First International Conference on Software, Systems and Information … , 2024
    2024.0
  • Provable, Reliable And Secure Data Aggregation Through Integrated Distributed Mechanism In Iot Based WSN Environment
    MB Kumara
    Webology 18 (6), 1657-1676 , 2021
    2021.0
  • Optimized Data Collection and Computation using Internet of Things (IoT)
    SAP Bharath Kumara
    https://www.ijitee.org/wp-content/uploads/papers/v8i10/J90470881019.pdf 8 … , 2019
    2019.0
  • 1 GHz Inverse Filters using Operational Amplifier
    B Kumara, P Goel, P Sharma
    2019.0
  • Performance analysis of 1.6 Tbps Optical Code Division Multiple Access system using Multi-Diagonal Code
    B Kumara, R Deelip
    2019.0
  • Smart home security system with fire emergency response
    B Kumara, J Kishan, PS Patil, R Shivani, D Monicapriya
    2019.0
  • Street Lamp Control through an Infrared Sensor
    SK Nayak, B Kumara
    SASTech-Technical Journal of RUAS 17 (2), 17-20 , 2018
    2018.0
  • An Overview on operational amplifier as Multivibrator
    RJ Bose, P Bikramjeet, B Kumara