Cyber risks are at an all-time high, with breaches getting more severe each year. As per IBM‘s 2022 report, the average cost of a data breach now exceeds $4 million. At the same time, attackers are using more sophisticated techniques powered by AI and machine learning. Legacy security tools are no match for these threats.
This is why next-gen technologies like process mining have become essential for cyber defense. Process mining analyzes event log data to model end-to-end processes and user behavior. It enables continuous monitoring to detect anomalies in real time. According to Gartner, 60% of digital businesses will leverage process mining for security and risk management by 2025.
In this comprehensive guide, I‘ll share the top 12 cybersecurity use cases for process mining based on my experience as a data analytics expert. For each use case, I‘ll cover:
- How it works: The underlying approach and methodology
- Impact: The business value delivered for security teams
- Examples: Real-world instances and results
Let‘s get started.
1. Identifying Security Breaches
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How it works: Process mining builds a baseline of normal user activities based on event logs. Deviations from normal behavior patterns are flagged as potential breaches for investigation.
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Impact: Early breach detection limits damage. A 2022 Ponemon study found that breaches identified in less than 200 days cost $3.05 million less than those discovered later.
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Example: A process model highlighted an employee accessing payroll systems outside the month-end pay run process. This unauthorized access was flagged and investigated as a data theft attempt.
2. Securing Industrial Control Systems
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How it works: Process mining uses ICS logs to model device communications, detect protocol violations, and uncover threats.
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Impact: Real-time monitoring ensures uptime and safety. Per IBM, industrial cyber incidents cost organizations $4.27 million on average.
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Example: An automotive plant used process mining to identify issues like PLCs transmitting unencrypted data and HMIs with vulnerable firmware.
3. Protecting IoT Environments
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How it works: Behavioral models discern compromised or misconfigured IoT devices. Data flow analysis detects malicious internal communications.
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Impact: IoT cyberattacks were up 700% in 2021, making process mining indispensable. It cuts response time from months to hours.
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Example: Process mining helped an energy company identify rogue IoT devices secretly mining cryptocurrency. Over 15% of their IoT fleet was breached.
4. Securing Smart Grids
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How it works: Analyzing smart meter logs, SCADA data, and network traffic reveals grid anomalies, outage causes, and cyber incidents.
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Impact: Grid attacks can impact millions of lives. Process mining improves resilience and incident response.
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Example: A cyberattack caused a grid failure that left 230,000 people without power. Using process mining, the root cause was identified as compromised field sensors.
5. Managing Mobile Security
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How it works: Monitoring device configurations, app behavior, network traffic and authentication events highlights mobile risks.
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Impact: Over a third of all records breached involve mobile devices. Process mining reduces mobile malware and data leakage.
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Example: Behavioral analysis revealed corporate emails being forwarded from managed mobile devices to personal accounts, indicating a data theft attempt.
6. Detecting Network Intrusions
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How it works: By turning network logs into a live process model, attacks are visualized as they unfold. Analysts can trace the attack path and impact.
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Impact: Process mining provides superior detection of network-based threats with up to 95% accuracy.
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Example: A ransomware attack was caught early by flagging abnormal RDP connections between systems that don‘t normally interact.
7. Blocking Web App Attacks
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How it works: User sessions and web transactions are modeled to detect spoofing, input attacks, unauthorized workflows etc.
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Impact: Process mining detects web app attacks missed by firewalls and WAFs, reducing incident response time by 62%.
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Example: A pharmacy website detected and blocked a credential stuffing attack after observing thousands of failed login attempts across user accounts in a short span.
8. Conducting Incident Investigation
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How it works: Building an attack process model from log data provides forensic visibility otherwise unavailable.
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Impact: Comprehensive insight into security incidents guides prevention and hardening.
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Example: By mining AWS CloudTrail logs, the blast radius and vulnerabilities exploited in a cryptojacking attack were uncovered.
9. Catching Insider Threats
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How it works: User activity monitoring reveals unauthorized data access, suspicious access timing, deviation from norms etc.
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Impact: Insider threats account for 34% of breaches. Early detection is critical.
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Example: An analyst downloaded 500 sensitive customer records outside normal working hours. Process mining flagged this as abnormal access for further review.
10. Detecting Financial Fraud
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How it works: Analyzing transactions, account activity, credit checks and more uncovers fraudulent patterns.
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Impact: Banking trojans and credential theft increased by 15X in 2024. Process mining is vital for fraud prevention.
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Example: A 50% YoY increase in loan approvals raised flags. Process mining revealed employees deliberately skipping credit history checks.
11. Strengthening Software Security
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How it works: By modeling code commits, builds, tests, and deployments, process mining finds security gaps in the SDLC.
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Impact: Over 80% of successful attacks exploit software vulnerabilities. Process mining helps developers build more secure code.
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Example: A telemetry data breach was found to be caused by error handling omission in a new feature that bypassed testing.
12. Error Detection in Systems
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How it works: Process models highlight crashes, failed logins, access denials, timeouts etc. that reflect vulnerabilities.
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Impact: Real-time error monitoring enables preemptive hardening.
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Example: Sporadic authentication failures, even for valid users, pointed to an expired TLS certificate in a payments application.
Key Takeaways
This overview demonstrates the immense value process mining delivers across diverse cybersecurity use cases by:
- Continuously monitoring systems and users to detect threats early
- Providing forensic visibility into attacks to strengthen defenses
- Uncovering configuration errors and data flows that create risks
- Automating analysis for faster response and proactive hardening
Forrester predicts that 60% of security analytics investments will focus on process mining capabilities by 2023. Major vendors like Celonis, UiPath, Minit, and QPR provide purpose-built solutions for cybersecurity.
To maximize returns, define high-impact use cases aligned to top risks and needs. Focus on high-value starting points like breach detection and threat hunting. Measure baseline metrics like mean time to detection and dwell time to track improvements.
With the right strategy, process mining serves as a force multiplier that makes security teams more productive and organizations much harder to breach.
Related Resources:
- Process Mining for Security & Risk Management
- 44 Process Mining Use Cases by Department
- Top Process Mining Vendors
- Process Mining Buyer‘s Guide
Let me know if you need help getting started with process mining or selecting the right platform for your security needs.