DR.REVATHI.S

@srmist.edu.in

Assistant Professor, Computer Science
SRM INSTITUTE OF SCIENCE AND TECHNOLOGY

DR.REVATHI.S


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https://researchid.co/reva1234

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Computer Science Applications
9

Scopus Publications

56

Scholar Citations

4

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Advancing environmental modeling: Integrating AI, big data, and predictive analytics for sustainable solutions
    S. Revathi, P. Pushpa, S. Saranya, V. Rekha, S. P. Santhoshkumar, Anto Gracious L. A., V. Sathya
    AI Methods for Environmental Protection and Resource Conservation, 2025
    Environmental modeling has a major importance in analyzing the changes in the environment, climate, and resource allocation. The current environmental models with the use of new technologies such as AI, machine learning, big data, and IoT improves the precision of climate change predictions, emissions, protection of species, and prevention of calamites. These models use data and information generated in real-time and computer models to arrive at policy recommendations. However, there are some limitations like data uncertainty, computational complexity, and the gaps between the existing and implemented policies that reduce their efficiency. Future research needs to address the issues of combining different types of AI, continuous monitoring of the AI-driven processes, and sharing of AI models due to the concerns related to the accessibility and accuracy of the results. At the international level, the development of environmental modeling hence requires interventions from interdisciplinary fields as the policy frameworks.
  • Environmental monitoring for sustainability: Technologies, trends, and future directions
    D. Ravindran, S. Revathi, V. Sowndharya, I. Farzhana, S. Swetha, R. Vinoth, R. Siva Subramanian
    Leveraging Urban Computing for Sustainable Urban Development, 2025
    Environmental monitoring is an essential activity in sustainability because it generates vital information about natural systems and enables people to meet important environmental needs like climatic change, pollution or depletion of biological diversity. This paper systematically reviews the state of the art on environmental monitoring technologies, methods, and trends and discusses how they contribute to sustainable solutions. Technologies that can be used are remote sensing technology, insitu monitoring, and (IOT) which can be used to acquire real time information on the quality of the air, water bodies and the ecosystem. This paper also highlights issues that are; data accuracy issues, integration, and ethical problems concerning with environmental monitoring technologies. This survey further explores the future trends such as; community based monitoring and AIdriven environmental systems hence indicating the need for further policy support and innovation in order to increase the efficiency of monitoring practices.
  • Fostering Democratic Transparency: A Secure Voting System with Aadhaar Cards on the Ethereum Blockchain Technology
    S. Revathi, V. R. ELangovan
    Lecture Notes in Networks and Systems, 2025
  • Block Chain Technology: Anomaly Detection in Bitcoin Using RFMLPAlgorithm
    V.R. Elangovan, S. Revathi, Nusrat Jabeen T, Ahmed J. Obaid, Rahul Kumar
    2024 International Conference on Emerging Trends in Networks and Computer Communications Etncc 2024 Proceedings, 2024
    Block chain technology has been used in many different fields, including banking, logistics, healthcare, and government. However, billions have been lost to cyber attacks on block chain apps in the last several years. An efficient approach for identifying malicious behavior in block chain networks is urgently required. Anomaly detection is a well-studied issue with a lengthy history of research. Anomalies are, in a nutshell, unusual or improbable occurrences. Theft and other illicit activity in financial networks are often outliers. Participants in the network want to spot anomalies as soon as possible to safeguard the overall safety and security of the system. However, fraud and anomaly detection techniques are constantly developing along with the financial industry. Furthermore, the most secure approach being brought into money is block chain technology. The number of scams, however, increases every year alongside these innovative technology. This is why we suggested a safe Anomaly detection technique that combines Machine Learning with Deep Learning. For the purpose of classifying Anomaly transactions, we used a unique hybrid RFMLP approach. For Bitcoin transaction anomaly detection, the RFMLP combines Random Forest (RF) with multilayer perceptron (MLP). We found that our RFMLP was more accurate than competing algorithms.
  • Unraveling the Quantum Computing Frontier: Advancements, Challenges, and Future Prospects
    D. Ravindran, S. Revathi, V. Sowndharya, I. Farzhana, V. Sathya, P. Girija, Siva Subramanian
    Integration of AI Quantum Computing and Semiconductor Technology, 2024
    Quantum computing, based on the theory of quantum mechanics, revolutionizes information processing with amazing computational power. This article addresses quantum computing and discusses its current and future advances. First, it defines quantum computing and explains qubits, quantum entanglement, and quantum gates. Next, it discusses the recent decade's technical advances in qubits, quantum supremacy, and key experiments. It also examines quantum algorithm's applications in cryptography, drug and gene discovery, material design, optimisation, and ML to demonstrate its potential to advance development. However, practical quantum computing confronts significant error rates, scalability limitations, and ethical concerns. This study examines these challenges and their solutions and preventives. It predicts quantum computing technology's growth, impact on many industries, and societal effects. This study seeks to improve knowledge of quantum computing and understanding quantum computing's limitations and prospects may improve it and create a new information processing method.
  • Identifying vulnerable user in linkedin using web description logic rule generation
    International Journal of Scientific and Technology Research, 2019
  • Privacy Protected System for Vulnerable Users and Cloning Profile Detection Using Data Mining Approaches
    M. Suriakala, S Revathi
    2018 10th International Conference on Advanced Computing Icoac 2018, 2018
    The evolution of Online Social Networks in recent years have lead to an enormous rise in users working on Facebook, LinkedIn and twitter etc.. Actively, it can be claimed that Internet projects itself as the ultimate mode of communication providing easy and user friendly exchange of information worldwide. The figures reveal that OSN namely Facebook, LinkedIn and twitter etc have minimum one profile among the 80% of active online users. Such users exchange and post information or write ups based on every days life related topics that vary from events, politics, news and celebrities. As far as OSN is concerned this kind of behavioral outlook is seriously refrained by the privacy settings concerning public profile data. These social network offers restrictive data related to user profile that is publically available. These networks face a big security challenge which is also a prime concern for the users too and that is the building up of fake accounts and hacking users personal data. The research paper suggests a Privacy Protected System technique which identifies malicious user and examines any sort of attack thus enhancing the security and making the network protected. Privacy protected System is categorized under 2 types: One is the vulnerable user protecting which detects malicious user while other being the Profile cloning identification and detection. The main motive of suggested Privacy Protected Systems being helping in vulnerable user detection yielding in greater detection rate on available intrusions along with the feature of detectors in detecting malicious attacks. The experiment reveals that by implementing our technique there was noticeable outcome in identifying unknown attacks that was higher than with detection rate as 97.29 % and below 1% of false alarm rate.
  • Profile Similarity Communication Matching Approaches for Detection of Duplicate Profiles in Online Social Network
    S. Revathi, Dr.M. Suriakala
    Proceedings 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions Csitss 2018, 2018
    In today’s world, the social life of people has close connection with the social networking Sites, for example, Facebook, Twitter and LinkedIn. Most of the social networks have weak user authentication technique, which mainly depends on fundamental details such as displayed user name and photo. Fake or unauthorized users abuse the authorized users’ details such as name, text messages, photographs and videos with or without the approved user’s consent. Profile cloning is a major security problem in social networks as it creates a profile which is homogeneous or similar to the existing ones. Profile cloning detection facilitates the chance to detect frauds in social networks, which can attract people’s trust to collect social data. In this paper an effort is accomplished to give an idea of profile cloning recognition in Online Social Networks (OSN) utilizing Network Theory. This study examines Node Similarity Communication Matching algorithm utilizing profile cloning recognition in Online Social Network depending on malicious user’s latest activities in the social network. In this proposed method, the various activities to be studied includes the activities such as Updates, Wall posts and comments, By recent activities etc. Malicious which hacks users’ identity is identified based on the comparison of threshold values of user’s personal profile attributes and network similarity analysis. The processes used in the research include Creating Account, user operation, monitoring, searching recent activity, Detecting cloned profile process, selecting profile to be examined, and deciding Real/Fake profile. The processes are additionally examined with experiments and the outcomes clearly revealed that the proposed algorithms are beneficial and effective when compared with the known methods. It is exhibited with large number of profile data that the method used can find the cloning profile with about 93.87% accuracy.
  • An intelligent and novel algorithm for securing vulnerable users of online social network
    S. REVATHI, M. SURIAKALA
    Proceedings of the 2nd International Conference on Computing Methodologies and Communication Iccmc 2018, 2018
    The last few years have witnessed a very fast-paced growth in the user base and activities of Online Social Networks (OSN). Their growth is attributed to the trust that they have received from people. People engage in social networks to make friends, chat, upload and like photos, update their status, and post comments. The use of social networks causes users to think less about the related security and privacy concerns in terms of OSNs. Trusting social networks leads to serious privacy concerns. Users disclose their information voluntarily, not knowing who exactly is going to access or use their data. They are less concerned about how safe their private information is, as they are more interested in meeting different people from across the globe. Their desire to connect with their family, friends, and virtual friends is apparent from their use of OSNs. The widespread use of social networks has also given rise to widespread impersonation. It is difficult to find a feasible solution to help counteract the negative consequences of this problem. This paper discusses the reasons behind information leaks, particularly, the way in which OSNs contribute to the intelligence used by hackers. A number of security measures for organizations are also included in the paper, to help them combat the activities related to leakage of information with respect to OSNs. It also identifies the future direction in terms of in-depth research in the fields by establishing a culture of security and implementing behavioral change. The Description Logic Rule Generation algorithm is proposed in the paper to be able to find and analyze the nature of vulnerabilities and attackers. The algorithm identifies vulnerable users on the basis of a sharing threshold. The users are removed in case they cross the threshold values. The paper also presents the security analysis of results of the OSNs popularity among users.

RECENT SCHOLAR PUBLICATIONS

  • Unraveling the Quantum Computing Frontier: Advancements, Challenges, and Future Prospects
    D Revathi.S
    Integration of AI, Quantum Computing, and Semiconductor Technology , 2025
    2025.0
    Citations: 10
  • Advancing Environmental Modeling: Integrating AI, Big Data, and Predictive Analytics for Sustainable Solutions
    D Revathi.S
    AI Methods for Environmental Protection and Resource Conservation , 2025
    2025.0
  • Environmental Monitoring for Sustainability: Technologies, Trends, and Future Directions
    D Revathi.S
    Leveraging Urban Computing for Sustainable Urban Development , 2025
    2025.0
    Citations: 4
  • AI-Powered Debugging and Optimization Tool for Software Development
    D Revathi.S
    IN Patent 202541040600 A , 2025
    2025.0
  • Fostering Democratic Transparency: A Secure Voting System with Aadhaar Cards on the Ethereum Blockchain Technology
    S Revathi, VR ELangovan
    International Conference on Mathematical Modeling and Computational Science … , 2025
    2025.0
  • Deep learning for image segmentation
    D Revathi.S
    Vol Machine Learning for Medical Applications Computer Vision, Image … , 2025
    2025.0
  • Networks and Security
    D Revathi.S
    2024.0
  • Block chain technology: Anomaly detection in bitcoin using rfmlpalgorithm
    VR Elangovan, S Revathi, N Jabeen, AJ Obaid, R Kumar
    2024 International Conference on Emerging Trends in Networks and Computer … , 2024
    2024.0
    Citations: 2
  • Database Management Concepts
    D Revathi.S
    2024.0
  • UNLOCKING THE POTENTIAL: EXAMINING THE PROSPECTS AND PITFALLS OF DECENTRALIZED VOTING SYSTEMS POWERED BY BLOCKCHAIN TECHNOLOGY
    DRACG DR.REVATHI.S
    Journal of the School of Language, Literature and Culture Studies 26 (4), 66 , 2024
    2024.0
  • Hybrid optimization using CC and PSO in cryptography encryption for medical images
    S Adhikari, M Brayyich, D Akila, B Sakar, S Devika, S Revathi
    International Conference on Mathematical Modeling and Computational Science … , 2023
    2023.0
    Citations: 6
  • SYSTEM AND METHOD FOR DETECTING FAKE VOTING USING MULTI-FACTOR AUTHENTICATION ENCRYPTED DATA DEVICE
    RK Dr.Revathi.S,Dr.L.Arulmozhiselvan,Dr. Ram Murat Singh,Mr.Sachin Sampat ...
    IN Patent App. 202,341,066,944 , 2020
    2020.0
  • Web Description Logic Rule Generation And Other Machine Learning Algorithms – A Comparative Study
    DMS Revathi. S
    International Journal of Advanced Trends in Computer Science and Engineering … , 2020
    2020.0
  • ANALYSIS ON DIFFERENT SECURITY ISSUES AND CHALLENGES IN SOCIAL NETWORK
    R S
    IJRAR 6 (1), 414-422 , 2019
    2019.0
  • Identifying Vulnerable User In Linkedin USING WEB DESCRIPTION LOGIC RULE GENERATION
    MS REVATHI.S
    IJSTR 8 (10), 1898-1904 , 2019
    2019.0
  • Profile similarity communication matching approaches for detection of duplicate profiles in online social network
    S Revathi, M Suriakala
    2018 3rd International Conference on Computational Systems and Information … , 2018
    2018.0
    Citations: 16
  • Privacy protected system for vulnerable users and cloning profile detection using data mining approaches
    M Suriakala, S Revathi
    2018 Tenth International Conference on Advanced Computing (ICoAC), 124-132 , 2018
    2018.0
    Citations: 14
  • An intelligent and novel algorithm for securing vulnerable users of online social network
    S Revathi, M Suriakala
    2018 Second International Conference on Computing Methodologies and … , 2018
    2018.0
    Citations: 4
  • Detecting Vulnerable User in Twitter Using Tweet Description Logic Rule Generation
    R S
    IOSR-JCE 20 (5), 27-35 , 2018
    2018.0
  • Preventing User Becoming Vulnerable By Measuring the User Behavior in OSN
    S Revathi, M Suriakala

MOST CITED SCHOLAR PUBLICATIONS

  • Profile similarity communication matching approaches for detection of duplicate profiles in online social network
    S Revathi, M Suriakala
    2018 3rd International Conference on Computational Systems and Information … , 2018
    2018.0
    Citations: 16
  • Privacy protected system for vulnerable users and cloning profile detection using data mining approaches
    M Suriakala, S Revathi
    2018 Tenth International Conference on Advanced Computing (ICoAC), 124-132 , 2018
    2018.0
    Citations: 14
  • Unraveling the Quantum Computing Frontier: Advancements, Challenges, and Future Prospects
    D Revathi.S
    Integration of AI, Quantum Computing, and Semiconductor Technology , 2025
    2025.0
    Citations: 10
  • Hybrid optimization using CC and PSO in cryptography encryption for medical images
    S Adhikari, M Brayyich, D Akila, B Sakar, S Devika, S Revathi
    International Conference on Mathematical Modeling and Computational Science … , 2023
    2023.0
    Citations: 6
  • Environmental Monitoring for Sustainability: Technologies, Trends, and Future Directions
    D Revathi.S
    Leveraging Urban Computing for Sustainable Urban Development , 2025
    2025.0
    Citations: 4
  • An intelligent and novel algorithm for securing vulnerable users of online social network
    S Revathi, M Suriakala
    2018 Second International Conference on Computing Methodologies and … , 2018
    2018.0
    Citations: 4
  • Block chain technology: Anomaly detection in bitcoin using rfmlpalgorithm
    VR Elangovan, S Revathi, N Jabeen, AJ Obaid, R Kumar
    2024 International Conference on Emerging Trends in Networks and Computer … , 2024
    2024.0
    Citations: 2
  • Advancing Environmental Modeling: Integrating AI, Big Data, and Predictive Analytics for Sustainable Solutions
    D Revathi.S
    AI Methods for Environmental Protection and Resource Conservation , 2025
    2025.0
  • AI-Powered Debugging and Optimization Tool for Software Development
    D Revathi.S
    IN Patent 202541040600 A , 2025
    2025.0
  • Fostering Democratic Transparency: A Secure Voting System with Aadhaar Cards on the Ethereum Blockchain Technology
    S Revathi, VR ELangovan
    International Conference on Mathematical Modeling and Computational Science … , 2025
    2025.0
  • Deep learning for image segmentation
    D Revathi.S
    Vol Machine Learning for Medical Applications Computer Vision, Image … , 2025
    2025.0
  • Networks and Security
    D Revathi.S
    2024.0
  • Database Management Concepts
    D Revathi.S
    2024.0
  • UNLOCKING THE POTENTIAL: EXAMINING THE PROSPECTS AND PITFALLS OF DECENTRALIZED VOTING SYSTEMS POWERED BY BLOCKCHAIN TECHNOLOGY
    DRACG DR.REVATHI.S
    Journal of the School of Language, Literature and Culture Studies 26 (4), 66 , 2024
    2024.0
  • SYSTEM AND METHOD FOR DETECTING FAKE VOTING USING MULTI-FACTOR AUTHENTICATION ENCRYPTED DATA DEVICE
    RK Dr.Revathi.S,Dr.L.Arulmozhiselvan,Dr. Ram Murat Singh,Mr.Sachin Sampat ...
    IN Patent App. 202,341,066,944 , 2020
    2020.0
  • Web Description Logic Rule Generation And Other Machine Learning Algorithms – A Comparative Study
    DMS Revathi. S
    International Journal of Advanced Trends in Computer Science and Engineering … , 2020
    2020.0
  • ANALYSIS ON DIFFERENT SECURITY ISSUES AND CHALLENGES IN SOCIAL NETWORK
    R S
    IJRAR 6 (1), 414-422 , 2019
    2019.0
  • Identifying Vulnerable User In Linkedin USING WEB DESCRIPTION LOGIC RULE GENERATION
    MS REVATHI.S
    IJSTR 8 (10), 1898-1904 , 2019
    2019.0
  • Detecting Vulnerable User in Twitter Using Tweet Description Logic Rule Generation
    R S
    IOSR-JCE 20 (5), 27-35 , 2018
    2018.0
  • Preventing User Becoming Vulnerable By Measuring the User Behavior in OSN
    S Revathi, M Suriakala