Network-Intrussion-Detector

🛡 Turning Curiosity into a Cyber Guardian It started with a question that kept bugging me for years: "How does an IDS really think?" 🤔 Fast forward — that curiosity has now grown into the Network Intrusion Detection Dashboard: a hands-on project where 23+ years in telecom meet the sharp edge of AI & ML. 💥 What it delivers: Sees what humans miss → Parses raw PCAP traffic into clean, analyzable data Thinks faster than threats → Threshold + ML-based anomaly detection Shows the invisible → PCA plots to uncover hidden traffic patterns Built to grow → From local parsing to hybrid detection and real-time alerts 📚 Lessons from the trenches: Garbage in = Garbage out → Data quality is king Heavy libraries? Plan them in from day zero Sampling saves dashboards (and your sanity) Logs are your best friend when things break Write code like you’ll hand it to your future self 🛠 Stack in play: Python (pandas, scikit-learn, pyshark), Streamlit, Plotly 📅 Next stops: Hybrid detection + real-time alerting 💌 Let’s talk shop: 📧 milzon.ltf@gmail.com 💻 https://lnkd.in/gm78wwDc 🙏 Special thanks to my handsome mentor Ramin Safarov and Qarir Generator QarirGenerator— for pushing me to turn an idea into something that actually bites back at cyber threats. and thanks my sifu master buddy Arli Ramdhani nur widiyanti Sulianto 梁紹豐 . NABIH IBRAHIM BAWAZIR Narendra Bayutama Wibisono Krina Wibisana @niko hashtag#CyberSecurity hashtag#MachineLearning hashtag#NetworkSecurity hashtag#Streamlit hashtag#AnomalyDetection hashtag#Python hashtag#PCA hashtag#DataVisualization hashtag#Telecom