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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | ATTACKS ON WEB LOG DATA: A REVIEW |
| Authors Name: | Diwakar Prasad Nuniya , Nisha |
| Unique Id: | IJSDR2305055 |
| Published In: | Volume 8 Issue 5, May-2023 |
| Abstract: | Many methods have been developed to protect web servers against attacks. Anomaly detection methods rely on generic user models and application behaviour, which interpret departures as indications of potentially dangerous behavior from the established pattern. In this paper, we conducted the use of a systematic review of the anomaly detection methods to prevent and identify web assaults; Many techniques of anomaly identification for automated log analysis have been suggested to minimize manual work. However, due to a lack of evaluations and comparisons of various anomaly detection techniques, engineers may still decide which detection methods should not be used. Furthermore, even if engineers use an unusual detection technique, re-implementation will take a lifetime. We offer a comprehensive analysis and evaluation of six existing log-based detection techniques, including three monitored and three unchecked modes, as well as an open toolkit that allows for simple reuse, to address these problems. These techniques were evaluated on two production log databases produced by the public, with a total of 15,923,592 log messages and 365,298 anomaly cases. We think that our work, as well as the testing results and associated discoveries, may be used as guidelines for adopting these strategies and as a source of inspiration for future research. |
| Keywords: | Anomaly Detection; Web Attacks; Log Anomaly, Web Content |
| Cite Article: | "ATTACKS ON WEB LOG DATA: A REVIEW", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 5, page no.357 - 364, May-2023, Available :http://www.ijsdr.org/papers/IJSDR2305055.pdf |
| Downloads: | 000222060 |
| Publication Details: | Published Paper ID: IJSDR2305055 Registration ID:206244 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: 357 - 364 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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