DETEKSI SERANGAN SQL INJECTION DENGAN APACHE SPARK MENGGUNAKAN METODE K-MEANS CLUSTERING

SYAUQI, BIMA GUSTI and Heryanto, Ahmad (2024) DETEKSI SERANGAN SQL INJECTION DENGAN APACHE SPARK MENGGUNAKAN METODE K-MEANS CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

Structured Query Language Injection or commonly called SQL Injection is a hacking technique to gain access to a SQL-based database system. Structured Query Language is a language used to create, process and manipulate databases. Because of this, detecting SQL injection attacks is the first and most important thing to do to combat SQL Injection attacks. The basis for conducting a detection approach is using machine learning. K-means clustering is the simplest and most well-known clustering analysis algorithm in solving clustering problems. This algorithm is known to be efficient for large datasets. This journal proposes the detection of SQL injection attacks using one of the unsupervised learning methods, namely K-means clustering on Apache Spark. This study uses the CIC-IDS2018 dataset from the University of New Brunswick (UNB) to train and experiment with the detection system used.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Keamanan Jaringan
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.A25 Computer security. Systems and Data Security. T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Bima Gusti Syauqi
Date Deposited:	03 Sep 2024 03:45
Last Modified:	03 Sep 2024 03:45
URI:	http://repository.unsri.ac.id/id/eprint/156493

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