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SmartShield IDS
AI-Powered Intrusion
Detection System

Enterprise-grade machine learning analytics dashboard for real-time network threat detection. Trained on CICIDS2017 with industry-leading 99.9% accuracy.

⚡ View ML Models 📬 Get Access
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Training Samples
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Feature Columns
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ML Models
// Machine Learning

ML Models Performance

Three high-performance classifiers trained on the CICIDS2017 dataset for network intrusion detection.

🌲
Random Forest
Best performing ensemble model
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% Accuracy
📉
Logistic Regression
Baseline linear classifier
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🧠
Neural Network (ANN)
Deep learning model (high precision)
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% Accuracy
// Analytics

ANN Performance Metrics

CLASSIFICATION METRICS

Accuracy 99.58%
Precision 98.90%
Recall 98.20%
F1 Score 98.50%

TRAINING DETAILS

Training Time22.1s
DatasetCICIDS2017
Total Samples2,830,743
Feature Count78
ArchitectureANN / MLP
Status✓ TRAINED
// Evaluation

Confusion Matrix

— PREDICTED —
ACTUAL ↓ Attack Normal
Attack
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True Positive
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False Positive
Normal
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False Negative
0
True Negative
Model Trained Successfully · High detection confidence
// Comparison

Model Comparison

Model Accuracy Precision Recall F1 Score Train Time
🌲 Random Forest 99.9% 98.2% 97.5% 97.8% 12.4s
📉 Logistic Regression 97.6% 96.1% 95.4% 95.7% 8.9s
🧠 Neural Network 99.6% 98.9% 98.2% 98.5% 22.1s
// Threat Intelligence

Cyber Attack Categories

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DoS / DDoS Attack
Overwhelms servers with traffic, causing denial of service for legitimate users.
HIGH RISK
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Brute Force Attack
Tries thousands of password combinations to gain unauthorized system access.
HIGH RISK
🕵️
MITM Attack
Intercepts communications between two parties to eavesdrop or manipulate data.
MEDIUM RISK
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SQL Injection
Inserts malicious SQL code into queries to access or destroy database contents.
HIGH RISK
🔍
Port Scanning
Probes a network to find open ports and identify potential vulnerabilities.
LOW RISK
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Botnet Activity
Coordinates infected devices to perform large-scale malicious operations.
HIGH RISK
// Data Source

CICIDS2017 Dataset

BENCHMARK DATASET
CICIDS2017

Real-world cybersecurity dataset used extensively for intrusion detection research. Contains labeled network traffic with both benign and attack patterns.

DoS DDoS Brute Force Port Scan Bot Web Attacks Infiltration

DATASET STATISTICS

2.83M
Total Samples
78
Features
15
Attack Types
2017
Release Year
// Contact
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