Skripsi
DETEKSI SERANGAN SMURF ATTACK MENGGUNAKAN ALGORITMA RANDOM FOREST
This final project focuses on detecting smurf attacks to be categorized as normal data or attacks. The smurf attack data packet is an ICMP packet, so in this study the focus is on the ICMP protocol. In making the dataset taken on the local network and divided into two datasets, namely normal datasets, and attack datasets. In performing detection, using ICMP message format in order to recognize attributes that are considered as attack patterns from smurf attacks such as frame length, icmp type, icmp identifier. So that attribute is used as a parameter in the classification with the random forest algorithm. The system that has been built with the random forest algorithm produces an accuracy rate of 99.99% of training data and 99.99% of testing data.
Inventory Code | Barcode | Call Number | Location | Status |
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2107004743 | T52750 | T527502021 | Central Library (REFERENCES) | Available but not for loan - Not for Loan |
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