ANALISA REAL-TIME DATA LOG HONEYPOT MENGGUNAKAN ALGORITMA K-MEANS PADA SERANGAN DISTRIBUTED DENIAL OF SERVICE
| Main Author: | Hermawan, Denni Septian |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/42336/1/PENDAHULUAN.pdf http://eprints.umm.ac.id/42336/2/BAB%20I.pdf http://eprints.umm.ac.id/42336/3/BAB%20II.pdf http://eprints.umm.ac.id/42336/4/BAB%20III.pdf http://eprints.umm.ac.id/42336/5/BAB%20IV.pdf http://eprints.umm.ac.id/42336/6/BAB%20V.pdf http://eprints.umm.ac.id/42336/ |
Daftar Isi:
- Cyber attacks on the internet are increasing. Various forms of cyber attacks will cause a disruption to the system which will cause the server to be unusable. Attacks that carry out continuous packet transmission with many computers such as Distributed Denial Of Service (DDoS) that are carried out by many hosts [3] will make the network unstable, even the network cannot be used because there are so many requests to meet the resource of the server. Honeypot can be used to detect and store information from DDoS attacks and then provide the results of a log data attack. The K-Means Clustering algorithm can group log data and group them into a data cluster that has the same time characteristics of a log of a Honeypot. From the cluster results and silhoulete coefficient calculation, network attacks are recorded in the second cluster with the value of the attack 845 with the highest attacker ip 210.124.164.133 of the total 7 clusters.