首页|Studies from Universitas AMIKOM Yogyakarta Provide New Data on Machine Learning (Comparative Analysis of the Performance of Decision Tree and Random Forest Algo rithms in SQL Injection Attack Detection)
Studies from Universitas AMIKOM Yogyakarta Provide New Data on Machine Learning (Comparative Analysis of the Performance of Decision Tree and Random Forest Algo rithms in SQL Injection Attack Detection)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators publish new report on artificial in telligence. According to news reporting fromthe Universitas AMIKOM Yogyakarta b y NewsRx journalists, research stated, “This study compares theperformance of t wo machine learning algorithms the Decision Tree and Random Forest.”The news reporters obtained a quote from the research from Universitas AMIKOM Yo gyakarta: “SQLInjection attacks continue to threaten web applications because t hey exploit vulnerabilities by injectingmalicious code into SQL statements exec uted on database servers. Therefore, machine learning algorithmsare used to ide ntify SQL Injection attacks. The dataset used is 33761 in the form of random que ry datainput in a CSV tabular containing sentence and label columns. The resear ch software used is GoogleColaboratory and Microsoft Edge. The series of resear ch conducted by Collect Data is data collection,Preprocessing handling missing values, deleting rows that contain duplicates, and the same query havingdiffere nt labels. Train and Test is used to build models and prepare test data, Build a nd Compile involvesbuilding Decision Tree and Random Forest models.”
Universitas AMIKOM YogyakartaAlgorithm sCyborgsEmerging TechnologiesMachine Learning
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