- Define Objectives & Scope: Pinpoint your OT cybersecurity needs and outline the scope of anomaly detection implementation.
- Data Collection & Preparation: Gather relevant OT data sources and ensure they're primed for analysis through cleaning and preprocessing.
- Select Anomaly Detection Techniques: Choose the right algorithms suited for OT environments, considering unique data patterns and security requirements.
- Model Training & Evaluation: Train your anomaly detection models using OT data and rigorously evaluate their performance against industry benchmarks.
- Integration & Deployment: Seamlessly integrate anomaly detection models into your OT systems for real-time monitoring and threat detection.
- Fine-tuning & Optimization: Continuously monitor and refine your models to adapt to evolving threats and ensure optimal performance.
- Documentation & Training: Document the implementation process thoroughly and provide training to OT teams to ensure effective utilization and response.
- Maintenance & Support: Establish robust maintenance protocols and offer ongoing support to sustain peak performance and address emerging threats.
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