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Image of KLASIFIKASI SERANGAN DDOS PADA APACHE SPARK MENGGUNAKAN METODE LONG SHORT TERM MEMORY

Skripsi

KLASIFIKASI SERANGAN DDOS PADA APACHE SPARK MENGGUNAKAN METODE LONG SHORT TERM MEMORY

Hanayuda, Dwi Lingga - Personal Name;

Penilaian

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Penilaian anda saat ini :  

Distributed Denial-of-Service (DDoS) attacks pose a serious threat to computer network infrastructures. Apache Spark, as a popular distributed data processing platform, requires effective methods to classify DDoS attacks on Apache Spark in order to enhance system security. In this research, we propose a classification approach using the Long-Short Term Memory (LSTM) method, data preprocessing with normalization, and dataset separation into training and testing data. We construct an optimized LSTM model architecture, which is trained using the training data and tested using the testing data to classify DDoS attacks. The CIC-IDS2018 dataset is used in this study. The experimental results demonstrate that the LSTM method achieves good performance in classifying DDoS attacks on Apache Spark. The LSTM model achieves high accuracy and exhibits good evaluation metrics such as precision, recall, and F1-score. Thus, the LSTM method can serve as an effective solution for securing Apache Spark against DDoS attacks.


Availability
Inventory Code Barcode Call Number Location Status
2307004076T1278172T1278172023Central Library (Reference)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1278172023
Publisher
Indralaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023
Collation
xiv, 77 hlm.; Ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
005.807
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Keamanan Data
Jurusan Sistem Komputer
Specific Detail Info
-
Statement of Responsibility
FIRA
Other version/related

No other version available

File Attachment
  • KLASIFIKASI SERANGAN DDOS PADA APACHE SPARK MENGGUNAKAN METODE LONG SHORT TERM MEMORY
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