Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India

Research Article

An Efficient Pre-processing Techniques on Log Server

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  • @INPROCEEDINGS{10.4108/eai.23-11-2023.2343237,
        author={Ganesh  V and Ashwanth Raj D and Venkata Krishnan R},
        title={An Efficient Pre-processing Techniques on Log Server},
        proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India},
        publisher={EAI},
        proceedings_a={IACIDS},
        year={2024},
        month={3},
        keywords={weblog server log files pre-processing user access patterns},
        doi={10.4108/eai.23-11-2023.2343237}
    }
    
  • Ganesh V
    Ashwanth Raj D
    Venkata Krishnan R
    Year: 2024
    An Efficient Pre-processing Techniques on Log Server
    IACIDS
    EAI
    DOI: 10.4108/eai.23-11-2023.2343237
Ganesh V1,*, Ashwanth Raj D1, Venkata Krishnan R1
  • 1: St Joseph's Institute of Technology, Department of ECE, Old Mahabalipuram Rd, Kamaraj Nagar, Chennai, Semmanjeri, Tamil Nadu
*Contact email: ganesh112302@gmail.com

Abstract

A biometric system for identifying fingers based on their unique veins under the skin is called finger vein recognition method (FVRM). Authentication is performed by scanning the finger with a special camera, and the information is checked on a registered visual collection. A total of two seconds is required to complete the process. A vein pattern is said to be more accurate than a fingerprint since it is based on veins under the surface of the skin. Fingerprint biometrics is a secure form of authentication, but it can be difficult to use in certain industries due to smudged fingerprints or cuts. FVRM method involves pre-processing techniques to enhance the standard of the veins snaps, as well as feature extraction steps to predict the contours of the finger veins Identification Details (ID)for authentication process. A Recurrent Neural Network is used for user authentication, and the Canberra distance classifier is used to measure the numerical distance between pairs of points. The proposed model will improve the accuracy for the authentication process, and the outputs are analysed using the confusion matrix.