From Detection to Prevention: Leveraging InfluxDB for Cybersecurity and IoT Threat Mitigation

By Suyash Joshi / Developer
Feb 13, 2025

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Cybersecurity in the Industrial Internet of Things (IIoT) is often overlooked despite powering critical infrastructure such as energy grids, telecom networks, factories, robotics, and aerospace, all of which are prime targets for cyberattacks and data breaches. A single breach can disrupt essential services or expose sensitive data.

So, how do we stay ahead of bad actors and proactively defend these systems? At the IoT Tech Expo 2025 in London, I had the opportunity to discuss these pressing challenges as part of the panel, “Transforming IoT Cybersecurity in 2025.” This blog builds on those insights by delving into SecOps, a specialized branch of DevOps focused on security.

Source: Cyber Physical System Design (Wikipedia)

Hypothetical IIoT architecture of industrial energy grid systems

1. Sensors and Data Security

  • Industrial sensors generate real-time temperature, voltage, pressure, and network activity data. Attackers can intercept or manipulate sensor readings, leading to data breaches or operational failures.

Example: In an energy grid, tampering with voltage sensors could cause cascading power failures.

2. Data Collection, Processing, & Storage

  • Event & Metric Data: Requires efficient time series storage of critical events and metrics related to sensor and application performance.

  • Processing: Huge amounts of streaming data are often processed before storage. This can easily be done using an open source tool like Telegraf over protocols like MQTT, SNMP, OPC-UA, and Modbus or even using ML Models on the edge.

  • Local vs. Cloud Data Storage & Processing: Local storage offers quicker response times, which is ideal for air-gapped environments. Cloud Storage offers centralized visibility, is easier in terms of scalability and compliance, and cloud vendors are delegated to deal with data security, encryption, etc.

  • Hybrid setup: Leverages the best of local and cloud. For instance, InfluxDB’s Edge Data Replication (EDR) feature ensures data is transmitted securely and synced between edge devices and central systems, even in low-connectivity environments.

3. Computing (Microcontrollers to Local Servers)

  • Microcontrollers (MCUs): Low-power devices handling data processing and security enforcement.

  • Edge Workstations/Servers: On-site data processing for real-time security decision-making before sending selective data to the cloud.

  • Private Networks: Critical IIoT infrastructure should operate on dedicated, non-shared private networks that are inaccessible to staff or external parties.

  • Air-Gapped Systems: Highly sensitive infrastructures should be air-gapped to prevent external attacks.

4. Network Monitoring & Alerting (Visualization, Firewalls, and Authentication)

  • Real-Time Monitoring Dashboards: Using something like Grafana to monitor security threats and system anomalies.
  • Network Security:
    • Firewalls and intrusion detection systems (IDS) to block unauthorized access.
    • Private Virtual Networks (PVN) for network segmentation to isolate critical infrastructure.
  • Authentication & Authorization:
    • Open source options like OAuth, Keycloak, or Vault for securing access.
    • API Credentials Security: Rotate keys, use least privilege principles, and secure endpoints.

10 key takeaways for IIoT SecOps

  • Secure Device Access: Never leave default credentials on IoT devices; enforce strong authentication mechanisms.
  • Network Protection: Implement firewalls, VPNs, and segmentation to prevent lateral movement of attackers.
  • 24x7 Monitoring & Alerts: Ensure real-time observability for detecting intrusions and triggering auto-remediation.
  • Leverage Machine Learning: Train models to detect network traffic and behavior anomalies and handle attacks, especially AI-generated bot attacks.
  • Conduct Security Audits: Perform regular Red Team vs. Blue Team exercises to simulate attacks and improve defenses.
  • Secure Data Transmission: Encrypt sensor data and implement secure communication protocols (TLS, VPN tunnels).
  • Network Separation & Intrusion Detection: Deploy IDS systems for real-time observability. Use private virtual networks (PVN) to separate critical infrastructure from non-essential systems.
  • Patch Management: Regularly update firmware and software from official sources to mitigate vulnerabilities.
  • Regulatory Compliance: Stay updated on IoT security regulations and industry standards to ensure compliance and ethical data handling.
  • Incident Response Planning: Establish a well-defined incident response plan to swiftly mitigate threats, minimize downtime, and maintain business continuity.

Conclusion & resources

As IIoT expands, so do cybersecurity risks. Organizations must adopt real-time monitoring, automated threat detection, and compliance-driven security to safeguard critical infrastructure.

InfluxDB supports these efforts by enabling efficient time series data management, enhancing visibility, and streamlining incident response. Whether deployed on-premises or in the cloud, a proactive cybersecurity strategy ensures IIoT systems remain secure, resilient, and adaptive in an interconnected world.

Additional Resources:

  1. Article on Machine learning to handle IoT security
  2. NCBI Paper on IIoT Security
  3. NIST Cybersecurity for IoT Report
  4. European Union’s Cyberreselient Act that deals with IoT Data security
  5. InfluxDB’s Security details