AI Driven Real Time Threat Assessment and Response Workflow

Real-Time Threat Assessment and Response

1. Threat Identification

1.1 Data Collection

Utilize AI-driven tools to gather data from various sources, including:

• Social media monitoring tools (e.g., Brandwatch)
• Threat intelligence platforms (e.g., Recorded Future)
• Customer feedback and review analysis (e.g., Revinate)

1.2 Anomaly Detection

Implement machine learning algorithms to detect unusual patterns or behaviors that may indicate potential threats.

• Example Tool: Darktrace – Uses AI to identify and respond to emerging threats in real-time.

2. Threat Analysis

2.1 Risk Assessment

Evaluate the identified threats based on their potential impact and likelihood of occurrence.

• Use AI-powered risk assessment tools (e.g., RiskLens) to quantify risks.

2.2 Contextual Analysis

Leverage AI to analyze the context of threats, including:

• Geolocation data
• Historical incident reports

Example Tool: IBM Watson – Provides contextual insights through natural language processing.

3. Response Strategy Development

3.1 Automated Response Planning

Utilize AI to develop automated response protocols based on predefined criteria.

• Example Tool: Splunk – Offers automated incident response capabilities.

3.2 Human Oversight

Incorporate a human review process to validate automated responses and ensure accuracy.

4. Incident Response

4.1 Real-Time Monitoring

Implement continuous monitoring systems to track the effectiveness of response actions.

• Example Tool: Sumo Logic – Provides real-time analytics and monitoring.

4.2 Communication Protocols

Establish clear communication channels for stakeholders during an incident.

• Example Tool: PagerDuty – Facilitates incident management and communication.

5. Post-Incident Review

5.1 Data Analysis

Analyze data from the incident to identify areas for improvement.

• Example Tool: Tableau – Visualizes incident data for comprehensive analysis.

5.2 Reporting and Documentation

Generate detailed reports on the incident response process and outcomes.

• Utilize AI-driven documentation tools (e.g., Confluence) for streamlined reporting.

6. Continuous Improvement

6.1 Feedback Loop

Incorporate feedback from incident reviews to enhance threat assessment and response protocols.

6.2 Training and Awareness

Implement ongoing training programs for staff on the use of AI security tools and incident response procedures.