3 Citations (Scopus)

Abstract

SQL injection is one of the biggest threats to websites. A survey shows more than 300,000 attacks, 24,6% are SQL injection. Detection SQL injection is a complicated task because attackers can continue to change the query structure. Traditionally, SQL injection is detected using a deny list of several keywords, which is commonly used for SQL injection. However, this method is not effective anymore because the attacks have increased significantly. This research develops a technique to detect SQL injection using TF-IDF and Bi-LSTM to produce high accuracy. Experiment results indicate that the proposed method improves SQL injection detection with accuracy, precision, recall, and F1-score reaching 0.99.

Original languageEnglish
Title of host publicationProceedings - 2022 7th International Conference on Information and Network Technologies, ICINT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages16-22
Number of pages7
ISBN (Electronic)9781665482844
DOIs
Publication statusPublished - 2022
Event7th International Conference on Information and Network Technologies, ICINT 2022 - Okinawa, Japan
Duration: 21 May 202223 May 2022

Publication series

NameProceedings - 2022 7th International Conference on Information and Network Technologies, ICINT 2022

Conference

Conference7th International Conference on Information and Network Technologies, ICINT 2022
Country/TerritoryJapan
CityOkinawa
Period21/05/2223/05/22

Keywords

  • Bi-LSTM
  • SQL Injection
  • TF-IDF

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