S.Arunprasath

@srmist.edu.in

research scholar and Department of Networking And Communications
SRM Institute of Science and Technology

S.Arunprasath


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https://researchid.co/arunprasathselvaraj

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Engineering, Computer Science Applications, Computer Networks and Communications
14

Scopus Publications

40

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Retraction note: Improving patient centric data retrieval and cyber security in healthcare: privacy preserving solutions for a secure future (Multimedia Tools and Applications, (2024), 83, 27, (70289-70319), 10.1007/s11042-024-18253-5)
    S. Arunprasath, Suresh Annamalai
    Multimedia Tools and Applications, 2026
  • Disp R-CNN for Personalized Care: A Deep Learning Approach to Fall Detection and Activity Recognition in AAL Systems
    S. Arunprasath, Suresh Annamalai
    Communications in Computer and Information Science, 2026
  • FLeX: A Federated Learning and Edge-Based Framework for Secure Cooperative Perception in 5G/6G-Enabled Vehicular Networks
    Kirithiga Nandini G, Gopinath N, Arunprasath S
    Proceedings of the 5th International Conference on Sentiment Analysis and Deep Learning Icsadl 2026, 2026
    Collaborative perception (CP) is essential for self-driving automobile systems, with V2X connected via 5 G and future 6 G communications technology. Yet cooperative CP systems are also subject to a problem of privacy; V2X communications are prone to security breaches while still needing to guarantee reliable network communications. To support cooperative CP and solve the V2X trilemma of privacy, robustness, and security, this study proposes FLeX, a Federated Learning and Edge based (FL/E) framework that combines a decentralized consensus based federated learning architecture (C-FL) with a Mobility Aware Robust Aggregation (MARA) technique; A Resource Adaptive Resource (ARA) scheme to enable model training that protects the privacy of users/operators by waiting until after training has been completed before sharing data. Extensive network simulations (NS3) and street simulations (SUM0) indicate that when compared against typical Federated Averaging algorithms, FLeX can achieve faster convergence times, higher packet delivery ratios, lower end-to-end delays and more accurate perception results than either one alone, suggesting that FLeX may provide an effective solution for safety critical intelligence transportation systems in the next generation of vehicles.
  • Improving patient centric data retrieval and cyber security in healthcare: privacy preserving solutions for a secure future
    S. Arunprasath, Suresh Annamalai
    Multimedia Tools and Applications, 2024
  • A Reliable Framework for Detection of Smart Contract Vulnerabilities for Enhancing Operability in Inter-Organizational Systems
    S. Arunprasath, A. Suresh
    Journal of Mobile Multimedia, 2024
    Information and communication technology based inter-organizational systems enable companies to integrate information and conduct business electronically across different parts of the organization. For organizations embracing blockchain, smart contracts provide automation and operational efficiency for inter-organizational systems. Initially utilised for financial transactions, smart contract are extended beyond banking and deployed in wide number of organizations. Smart contracts are regarded as self-executing type of contract consisting of agreement’s terms embedded directly into the code which plays a vital role in operability for inter-organizational systems, however, smart contract vulnerabilities can arise due to programming errors, leading to security issues. The effects of smart contract vulnerabilities can be significant, including loss of funds, unauthorized access to sensitive information, manipulation of data, and loss of trust in the application leading to catastrophic financial losses followed by legal implications for an organization based on blockchain technology. The goal of smart contracts exploiting vulnerabilities is to discover and eliminate potential security vulnerabilities in smart contract code prior to it being deployed. Detecting vulnerabilities in a timely manner helps to prevent financial losses, unauthorized access, and data manipulation. In order to provide a robust solution to detect vulnerabilities in smart contracts, the proposed methodology presents a novel approach for rapid detection of vulnerabilities by integrating genetic algorithm with isolation forest. Furthermore, enhancing smart contract vulnerability identification with higher accuracy and false-positive rate provides a reliable gateway for organizations to adopt blockchain.
  • Multimodal Sentiment Analysis: A GRU Approach for Improved Accuracy
    Nalini Manogaran, Suresh Annamalai, Anbarasu V, Resmi R Nair, Balamurugan Balusamy, Parimala Veluval, Sushamass Sushamass, Arunprasath S
    2024 International Conference on Electrical Electronics and Computing Technologies Iceect 2024, 2024
    In the real world, data often comes in different forms, such as text, audio, and video, making it multi-modal. This poses a challenge for machine learning models, which need to be able to process and understand this type of data. One way to address this challenge is to use models that can handle multiple data types in a single model. This enables the model to learn from the diverse information offered by the various data types. This research explores various methods for sentiment analysis in a multi-modal context, incorporating text, images, and potentially audio data. The methods evaluated include lexicon-based methods, machine learning with text features, convolutional neural networks (CNNs) for text, and a proposed multi-modal GRU model. The objective of the multi-modal GRU model is to surpass existing methods by efficiently capturing and integrating sentiment information from various modalities. The evaluation of the model's capabilities and constraints encompasses multiple performance indicators, including accuracy, precision, recall, and F1-score. Our Multi-modal GRUs model achieved an accuracy rate of 85%, precision of 82%, recall of 80%, and an F1-score of 81%. These metrics indicate that the model adeptly captures the underlying patterns within the multimodal data.
  • Quantum Teleportation and EntanglementBased Quantum Blind Signature Protocol for Quantum Secure Communication in Security Service Bases
    Sumathy G, Suresh A, Udendhran R, Maheshwari A, Arun Prasath Selvaraj
    ACM International Conference Proceeding Series, 2023
    Quantum teleportation and entanglement-based quantum blind signature protocol were promising new technologies for secure communication between security service bases. They were secure against a variety of attacks, including eavesdropping, signatory disavowal, verifier denial, and forgery. The protocol worked by using quantum entanglement to create a shared secret state between the security service bases. This shared secret state was then used to generate a quantum signature for each message sent between the bases. The signature was then verified by the receiving base using the shared secret state. Compared to classical blind signature schemes, the main advantages of the quantum entanglement-based quantum blind signature protocol were its information-theoretic security and reduced complexity and noise. However, this protocol also faced some challenges, such as preparing and storing entangled states, performing quantum operations and measurements, and ensuring the trustworthiness of the third party. Despite these challenges, the quantum entanglement-based quantum blind signature protocol was a promising new technology for secure communication between security service like military bases. It had the potential to revolutionize the way that military bases communicated with each other, making it possible to send secure messages without revealing the content or identity of the messages.
  • Interference techniques based on deep learning in wireless networks
    S. Arunprasath, A. Suresh, Jayden Khakurel
    Resource Management in Advanced Wireless Mobile Networks, 2023
    On small-scale wireless networks, traditional architectures deliver fast execution and nearly ideal performance, but when user density is high, the performance suffers significantly. The highly congested frequency band is one of the major problems for wireless communication technology. Numerous wireless users to share the same services in terms of time and/or frequency because of the constrained radio band. Interference develops from this configuration. The rising need for high data-rate transmission is driving current development in wireless communication technology. This has led to a major improvement in wireless networks’ performance in recent years. However, there is still a pressing demand for more effective wireless communications given the widespread usage of smart phones, laptops, and multimedia devices. For numerous networks, including cellular networks, wireless lan, and wireless ad-hoc networks, communication inside the presence significant interference has indeed been taken into consideration. One of the finest techniques for reducing wireless communication interference is deep learning. Each one operates by taking lessons from a dataset. One of the cutting-edge technologies that has been applied to address current wireless communication problems is deep learning. Deep learning employs two distinct methods: data-driven approach and model-driven approach. Neural networks were used in place of the traditional building blocks in the data-driven approach. The second method is the model-driven approach, which substitutes a neural network for parts of the traditional algorithms’ strategies.
  • Towards Reliable Medical Transactions for Blockchain based Healthcare Systems using Hybrid Consensus Method
    Arun Prasath Selvaraj, Suresh Annamalai
    ACM International Conference Proceeding Series, 2022
    Blockchain technology opens the door to securing and protecting massive amounts of IoT data storage, improving decentralized storage applications, getting rid of centralized trust servers, and facilitating data accountability and traceability. A hybrid blockchain can be used to build a network where sensors communicate with a device that performs smart contracts and records all events on the blockchain. Actual clinical observation and treatment choices would be provided by alerting patients and medical professionals and keeping a safe history of who started these acts. The proposed work aggrandize blockchain consensus algorithm that combines the benefits of the PoW and PoA algorithms. These PoW-PoA hybrid consensus methods are simulated with Merkle tree creation focusing conditional contrast large item set tree. The PoW mining mechanism is effectively utilized in proposed system to control the block creation time. With PoA consensus technique, the user generates the real blocks. The validating nodes, which are arbitrary chosen as reliable entities, protect PoA blockchain. The Proof of Authority concept is a highly scalable system since it only requires a small number of block validators. Participants who have been pre-approved serve as the system's moderators and confirm blocks and transactions. According to results, the proposed method performs better than conventional consensus algorithm in terms of scalability, network throughput, and the quantity of blocks generated.
  • Fabrication, characterization and regression modelling of aluminium matrix hybrid composites
    S. Arun Prasath, V. Veeranaath, K. Pavan Teja, Bijay Prasad
    Aip Conference Proceedings, 2022
    Aluminium based hybrid composites are most commonly active in aerospace and auto applications because of their extraordinary and noteworthy mechanical and thermal characteristics. However, the processing of these composites with ceramic and metal filers is a challenging task with unvarying reinforcement distribution and improved interfacial bonding. So, this paper is mainly concentrated to develop and study the effect of alumina and metal fillers in Al base. Al hybrid composites are processed by reinforcing identical fractions of alumina and metal fillers. Stir casting is employed for the processing of the same hybrid composites. Four samples were developed by varying the various processing constraints like stirring rate and duration and reinforcement content. The built samples were tested for hardness, wear rate and density. The dispersals of fillers in the matrix phase were characterized using SEM analysis. Taguchi analysis was employed to analyse the effect of several dispensation constraints on the production responses. Regression modelling is also employed for the prediction study of responses.
  • Wear and Tensile Behaviour of Aluminium Matrix Hybrid Composites
    S. Arunprasath, V. Veeranaath, K. Pavan Teja, Bijay Prasad
    International Journal of Vehicle Structures and Systems, 2022
  • Mechanical Properties of Graphene with Defects and Its Application in Nanocomposites-Brief Overview.
    S Arun Prasath, G Rajasekaran
    Iop Conference Series Materials Science and Engineering, 2020
  • Evaluation of mechanical properties on banyan fiber reinforced polymer matrix composite using FEA
    S Arun Prasath, V Balamurugan, S Sanjay Ganesh, A Udhaya Murthy
    Iop Conference Series Materials Science and Engineering, 2018
  • Effects of single point cutting tool materials on tool work interface and cutting performance using FEA
    S Arun Prasath, Ankit Kumar, Hemanta Deka, Abhishek Lahkar
    Iop Conference Series Materials Science and Engineering, 2018

RECENT SCHOLAR PUBLICATIONS

  • Retraction Note: Improving patient centric data retrieval and cyber security in healthcare: privacy preserving solutions for a secure future
    S Arunprasath, S Annamalai
    Multimedia Tools and Applications 85 (5), 435 , 2026
    2026.0
  • Interference Techniques Based on Deep Learning in Wireless Networks
    S Arunprasath, A Suresh, J Khakurel
    Resource Management in Advanced Wireless Networks, 161-182 , 2025
    2025.0
    Citations: 2
  • Disp R-CNN for Personalized Care: A Deep Learning Approach to Fall Detection and Activity Recognition in AAL Systems
    S Arunprasath, S Annamalai
    International Conference on Computer Vision and Image Processing, 138-151 , 2024
    2024.0
  • Multimodal Sentiment Analysis: A GRU Approach for Improved Accuracy
    N Manogaran, S Annamalai, RR Nair, B Balusamy, P Veluval, ...
    2024 International Conference on Electrical Electronics and Computing … , 2024
    2024.0
    Citations: 1
  • Improving patient centric data retrieval and cyber security in healthcare: privacy preserving solutions for a secure future
    S Arunprasath, S Annamalai
    Multimedia Tools and Applications 83 (27), 70289-70319 , 2024
    2024.0
    Citations: 29
  • Quantum Teleportation and EntanglementBased Quantum Blind Signature Protocol for Quantum Secure Communication in Security Service Bases
    S Sumathy, G., Suresh, A., Udendhran, R., Maheshwari, A., Arunprasath
    ACM International Conference Proceeding Series 56, 1 - 10 , 2024
    2024.0
    Citations: 1
  • A Reliable Framework for Detection of Smart Contract Vulnerabilities for Enhancing Operability in Inter-Organizational Systems
    S Arunprasath, A Suresh
    Journal of Mobile Multimedia 20 (2), 411-433 , 2024
    2024.0
    Citations: 4
  • IOT BASED FERROUS AND NONFERROUS WASTE SORTING MACHINE
    MRAS DR. SURESH ANNAMALAI,DR. ANBARASU VENKATACHALAM,DR. UDENDHRAN RAJENDRAN ...
    GB Patent App. 6,321,754 , 2023
    2023.0
  • DISASTER RISK REDUCTION AND MANAGEMENT
    SA Sriram Kumar K Krishna Sankar P
    https://www.researchgate.net/publication … , 2023
    2023.0
  • Full Stack Web Development with Hands-On Lab
    SA Sriram Kumar K Krishna Sankar P, Nithyanantham Sampathkumar
    https://www.researchgate.net/publication … , 2023
    2023.0
  • Towards Reliable Medical Transactions for Blockchain based Healthcare Systems using Hybrid Consensus Method
    AP Selvaraj, S Annamalai
    Proceedings of the 4th international conference on information management … , 2022
    2022.0
    Citations: 3
  • Artificial Intelligence and Machine Learning
    NS S Arunprasath Krishna Sankar P
    https://www.researchgate.net/publication … , 2022
    2022.0
  • Big Data Analytics
    SA Krishna Sankar P, Sriram Kumar K
    https://www.researchgate.net/publication/337652202_Big_Data_Analytics , 2019
    2019.0
  • Information Management
    AS Sriram Kumar K Krishna Sankar P
    2017.0
  • DISASTER MANAGEMENT
    SKK Arunprasath S Krishna Sankar P
    ARS Publications , 2017
    2017.0
  • Foundation Skills in Integrated Product Development
    KSRK S. Arun prasath P. Krishna Sankar
    2016.0
  • Cache Invalidation Mechanisms for maintaining Cache Consistency in Wireless Mobile Environments
    PS Prakashkumar, R Naraesh, S Arunprasath, R Dhamodharan

MOST CITED SCHOLAR PUBLICATIONS

  • Improving patient centric data retrieval and cyber security in healthcare: privacy preserving solutions for a secure future
    S Arunprasath, S Annamalai
    Multimedia Tools and Applications 83 (27), 70289-70319 , 2024
    2024.0
    Citations: 29
  • A Reliable Framework for Detection of Smart Contract Vulnerabilities for Enhancing Operability in Inter-Organizational Systems
    S Arunprasath, A Suresh
    Journal of Mobile Multimedia 20 (2), 411-433 , 2024
    2024.0
    Citations: 4
  • Towards Reliable Medical Transactions for Blockchain based Healthcare Systems using Hybrid Consensus Method
    AP Selvaraj, S Annamalai
    Proceedings of the 4th international conference on information management … , 2022
    2022.0
    Citations: 3
  • Interference Techniques Based on Deep Learning in Wireless Networks
    S Arunprasath, A Suresh, J Khakurel
    Resource Management in Advanced Wireless Networks, 161-182 , 2025
    2025.0
    Citations: 2
  • Multimodal Sentiment Analysis: A GRU Approach for Improved Accuracy
    N Manogaran, S Annamalai, RR Nair, B Balusamy, P Veluval, ...
    2024 International Conference on Electrical Electronics and Computing … , 2024
    2024.0
    Citations: 1
  • Quantum Teleportation and EntanglementBased Quantum Blind Signature Protocol for Quantum Secure Communication in Security Service Bases
    S Sumathy, G., Suresh, A., Udendhran, R., Maheshwari, A., Arunprasath
    ACM International Conference Proceeding Series 56, 1 - 10 , 2024
    2024.0
    Citations: 1
  • Retraction Note: Improving patient centric data retrieval and cyber security in healthcare: privacy preserving solutions for a secure future
    S Arunprasath, S Annamalai
    Multimedia Tools and Applications 85 (5), 435 , 2026
    2026.0
  • Disp R-CNN for Personalized Care: A Deep Learning Approach to Fall Detection and Activity Recognition in AAL Systems
    S Arunprasath, S Annamalai
    International Conference on Computer Vision and Image Processing, 138-151 , 2024
    2024.0
  • IOT BASED FERROUS AND NONFERROUS WASTE SORTING MACHINE
    MRAS DR. SURESH ANNAMALAI,DR. ANBARASU VENKATACHALAM,DR. UDENDHRAN RAJENDRAN ...
    GB Patent App. 6,321,754 , 2023
    2023.0
  • DISASTER RISK REDUCTION AND MANAGEMENT
    SA Sriram Kumar K Krishna Sankar P
    https://www.researchgate.net/publication … , 2023
    2023.0
  • Full Stack Web Development with Hands-On Lab
    SA Sriram Kumar K Krishna Sankar P, Nithyanantham Sampathkumar
    https://www.researchgate.net/publication … , 2023
    2023.0
  • Artificial Intelligence and Machine Learning
    NS S Arunprasath Krishna Sankar P
    https://www.researchgate.net/publication … , 2022
    2022.0
  • Big Data Analytics
    SA Krishna Sankar P, Sriram Kumar K
    https://www.researchgate.net/publication/337652202_Big_Data_Analytics , 2019
    2019.0
  • Information Management
    AS Sriram Kumar K Krishna Sankar P
    2017.0
  • DISASTER MANAGEMENT
    SKK Arunprasath S Krishna Sankar P
    ARS Publications , 2017
    2017.0
  • Foundation Skills in Integrated Product Development
    KSRK S. Arun prasath P. Krishna Sankar
    2016.0
  • Cache Invalidation Mechanisms for maintaining Cache Consistency in Wireless Mobile Environments
    PS Prakashkumar, R Naraesh, S Arunprasath, R Dhamodharan