Wijaya, Krisna Badru (2022) Penggunaan Data Kotor untuk Melatih Sistem Deteksi Serangan Berbasis Jaringan. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Keamanan sistem dan jaringan merupakan hal yang sangat penting untuk dijaga oleh setiap perangkat yang terhubung ke jaringan. Kemudahan akses pada jaringan menjadi pintu terbuka untuk pelaku-pelaku kejahatan siber melakukan serangan terhadap perangkat targetnya. Berbagai jenis serangan dapat ditemui secara sadar atau tidak sadar saat mengakses data pada jaringan. Dikarenakan banyaknya jenis data dan koneksi yang terjadi di jaringan, sangat sulit untuk membedakan antara koneksi yang normal dan koneksi yang tidak normal pada jaringan.
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Every device connected to the network need to maintain their network security system very well. Ease of access to the network is an open door for cybercriminals to carry out attacks on their target devices. Various types of attacks can be encountered consciously or unconsciously when accessing data on the network. Due to the large number of variety data and connections that occur on the network, it is very difficult to distinguish between normal connections and abnormal connections on the network. In order to prevent cybercrimes that can cause harm to user devices, every device connected to the network must be able to identify the security of the incoming connection.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | NIDS, machine learning, noisy data, data train, NIDS, machine learning, data kotor, data latih. |
| Subjects: | Q Science > QA Mathematics > QA76.9.A25 Computer security. Digital forensic. Data encryption (Computer science) |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Krisna Badru Wijaya |
| Date Deposited: | 08 Feb 2023 13:05 |
| Last Modified: | 08 Feb 2023 13:05 |
| URI: | http://repository.its.ac.id/id/eprint/96445 |
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