IMPLEMENTASI NETWORK TRAFFIC ANALISIS UNTUK MENDETEKSI ANOMALI JARINGAN PADA TWITTER/X DAN INSTAGRAM
DOI:
https://doi.org/10.25134/digibe.v2i2.31Keywords:
Anomali Jaringan, Wireshark, Twitter/X, InstagramAbstract
Abstrak
Penelitian ini berfokus pada implementasi analisis lalu lintas jaringan menggunakan Wireshark untuk mendeteksi anomali pada aplikasi Twitter/X dan Instagram. Tujuan utamanya adalah mengidentifikasi tingkat lalu lintas pada port-port yang ditandai dengan warna hitam dan merah, yang dapat mengindikasikan potensi masalah atau aktivitas jaringan mencurigakan. Penelitian ini menggunakan pendekatan kuantitatif dengan mengumpulkan data lalu lintas jaringan, melakukan analisis statistik, dan menerapkan teknik deteksi anomali. Hasil penelitian diharapkan dapat membantu mengidentifikasi dan mengatasi tingkat lalu lintas tinggi, serta memberikan wawasan berharga tentang keamanan jaringan dan strategi yang lebih efektif untuk mendeteksi dan mengatasi ancaman keamanan. Dalam analisis jaringan menggunakan Wireshark, terdapat beberapa fitur dan indikator warna yang membantu dalam memeriksa dan menganalisis lalu lintas paket data. Port berwarna biru muda menunjukkan "Sample inactive selected item," yang memungkinkan pengguna untuk melihat contoh isi paket yang tidak aktif, berguna untuk penelusuran paket tidak aktif, analisis payload data, dan pemecahan masalah jaringan. Port berwarna abu-abu menunjukkan "Sample active selected item," yang menampilkan contoh isi paket yang sedang aktif, membantu dalam pemeriksaan konten paket aktif, analisis payload data, dan pemahaman konteks komunikasi. Port berwarna hitam dan merah menunjukkan tingkat lalu lintas yang tinggi, dengan port hitam mungkin mencurigakan dan port merah menunjukkan potensi masalah seperti serangan DDoS atau kemacetan jaringan. Port merah ditandai dengan status flag "Reset = Set" dalam header TCP, mengindikasikan kemungkinan gangguan konektivitas, kesalahan konfigurasi perangkat, aktivitas mencurigakan, atau masalah pada endpoint komunikasi.
Kata kunci: Anomali Jaringan; Wireshark; Twitter/X; Instagram
Abstract
This research focuses on implementing network traffic analysis using Wireshark to detect anomalies in the Twitter/X and Instagram applications. The main goal is to identify traffic levels on ports marked in black and red, which can indicate potential problems or suspicious network activity. This research uses a quantitative approach by collecting network traffic data, conducting statistical analysis, and applying anomaly detection techniques. The research results are expected to help identify and address high traffic levels, as well as provide valuable insights into network security and more effective strategies for detecting and addressing security threats. In network analysis using Wireshark, there are several features and color indicators that help in examining and analyzing data packet traffic. The light blue port indicates “Sample inactive selected item,” which allows users to view a sample of inactive packet contents, useful for inactive packet tracing, data payload analysis, and network troubleshooting. The grayed port indicates “Sample active selected item,” which displays a sample of currently active packet contents, assisting in active packet content inspection, data payload analysis, and understanding the communication context. Black and red ports indicate high levels of traffic, with black ports possibly suspicious and red ports indicating potential problems such as DDoS attacks or network congestion. Red ports are indicated by the status flag "Reset=Set" in the TCP header, indicating possible connectivity disruption, device misconfiguration, suspicious activity, or problems with the communications endpoint.
Keyword: Network Anomalies; Wireshark; Twitter/X; Instagram
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