Cyber-Security in the Age of AI: Defense Strategies

AI-Powered Threat Detection

Modern intrusion detection systems leverage machine learning for anomaly detection:

// Anomaly detection using TensorFlow.js
import * as tf from '@tensorflow/tfjs';

class AnomalyDetector {
  constructor(threshold = 0.8) {
    this.threshold = threshold;
    this.model = null;
  }

  async loadModel(url) {
    this.model = await tf.loadLayersModel(url);
  }

  async detectAnomaly(networkTraffic) {
    const tensor = tf.tensor2d([networkTraffic]);
    const prediction = this.model.predict(tensor);
    const score = await prediction.data();
    
    return {
      isAnomaly: score[0] > this.threshold,
      confidence: score[0],
      timestamp: Date.now()
    };
  }
}

Real-time Monitoring

Deploy at scale using event-driven architecture for sub-100ms response times.

Key Takeaways

• ML models detect zero-day exploits
• Real-time processing is critical
• Human oversight remains essential