Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Alex Sandro Irawan
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Pengembangan Intrusion Detection System Terhadap SQL Injection Menggunakan Metode Learning Vector Quantization Alex Sandro Irawan; Eko Sakti Pramukantoro; Ari Kusyanti
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1205.243 KB)

Abstract

Database is a collection of systematic data stored in a computer. Database becomes popular in its implementation on the network because the user can access data on the database without need to store data on each user's computer. But the impact of ease of access, the database is also likely to be exposed to external threats by irresponsible people. One such threat is injection. SQL injection is one of the suspicious actions that exploit vulnerabilities in the SQL database. The most commonly used detection method today is to apply rules that aimed at preventing actions that harm a SQL database. However, these rules are not always effective, especially for new SQL injection methods. For that we need a system that can adapt to the new types of attacks based on existing attack data. Intrusion detection system that can adapt to new types of SQL injection attacks. The author implements an intrusion detection system using learning vector quantization method and tests it on a local network. The test results show an accuracy of 80%.
Co-Authors ari kusyanti Pramukantoro, Eko Sakti