Skripsi
DETEKSI SERANGAN FLOODING PADA JARINGAN SMART HOME IPv6 MENGGUNAKAN METODE DECISION TREE
The ICMPv6 "Packet TOO BIG" flooding attack presents a significant threat to IPv6 network security, especially when leveraging vulnerabilities in the EUI-64-based automatic address configuration and the Privacy Extension feature. In this type of attack, a single fixed source is used to send a high volume of malicious ICMPv6 packets to multiple destination addresses that share a similar address structure, exploiting both the deterministic nature of the EUI-64 format and weaknesses in packet handling. This can result in excessive network load and reduced performance. To address this, the study employs a simulated dataset to detect such attacks using the Decision Tree algorithm. The model is trained on labeled traffic data consisting of two categories: Benign and Flood. Evaluation results demonstrate an overall accuracy of 92.38%, with the Benign class achieving a precision of 100% and recall of 84.74%, while the Flood class attains a precision of 86.77% and recall of 100%. The F1-Score reflects balanced detection performance, with 91.70% for the Benign class and 92.91% for the Flood class.
Inventory Code | Barcode | Call Number | Location | Status |
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2507005530 | T183431 | T1834312025 | Central Library (Reference) | Available but not for loan - Not for Loan |
Title | Edition | Language |
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SISTEM PENCEGAHAN SERANGAN REMOTE TO LOCAL (R2L) DENGAN METODE DECISION TREE | id | |
VALIDASI SILANG PENGELOMPOKKAN JENIS KALENG MENGGUNAKAN METODE DECISION TREE | id |