Paper Title
Anomaly Detection in Car Booking System
Article Identifiers
Authors
Chetan Santosh Sahu , Nurussaba Sayyad , Girish Rakshit , Mayur Atalkar , Rahul Bambodkar
Keywords
Anomaly detection, Car booking system, Security, Reliability, Machine learning algorithms, Data analytics, Fraudulent transactions, Unauthorized access, System malfunctions, Fluctuating demand patterns, Geographical factors, Financial transactions security
Abstract
The escalating reliance on digital platforms for car booking services necessitates the development of robust anomaly detection mechanisms to ensure system security and reliability. This research is dedicated to crafting and deploying advanced anomaly detection techniques tailored to the distinctive characteristics of car booking systems. Utilizing machine learning algorithms and data analytics, the study targets the identification and mitigation of anomalous activities, including fraudulent transactions, unauthorized access, and system malfunctions. The research methodology involves the analysis of historical booking data to establish baseline behavior patterns, employing anomaly detection models to discern deviations from the norm. Special consideration is given to challenges inherent in the car booking domain, such as dynamic user behavior, fluctuating demand patterns, and diverse geographical factors. The proposed anomaly detection framework is designed for adaptability and evolution over time, ensuring effectiveness in detecting emerging threats and evolving attack vectors. Through the implementation of this system within existing car booking platforms, the research aims to fortify the overall security posture, safeguarding user data, financial transactions, and system integrity. The anticipated outcomes promise valuable contributions to the broader field of anomaly detection in digital service ecosystems, fostering a more secure and reliable environment for users and service providers alike.
Downloads
How To Cite (APA)
Chetan Santosh Sahu, Nurussaba Sayyad , Girish Rakshit , Mayur Atalkar , & Rahul Bambodkar (April-2024). Anomaly Detection in Car Booking System . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b897-b901. https://ijnrd.org/papers/IJNRD2404209.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : b897-b901
Other Publication Details
Paper Reg. ID: IJNRD_215405
Published Paper Id: IJNRD2404209
Downloads: 000121980
Research Area: Engineering
Country: Nagpur , Maharashtra , India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404209.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404209
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG
Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
Publication Timeline
Article Preview: View Full Paper
Call For Paper
IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.
The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.
Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.
How to submit the paper?
By Our website
Click Here to Submit Paper Online
Important Dates for Current issue
Paper Submission Open For: October 2025
Current Issue: Volume 10 | Issue 10 | October 2025
Impact Factor: 8.76
Last Date for Paper Submission: Till 31-Oct-2025
Notification of Review Result: Within 1-2 Days after Submitting paper.
Publication of Paper: Within 01-02 Days after Submititng documents.
Frequency: Monthly (12 issue Annually).
Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.
Subject Category: Research Area
Call for Paper: More Details
