AI Revolutionizes WAF Log Analysis, Cutting Manual Efforts by Over 90%

Transforming WAF Log Management with AI

The landscape of cybersecurity is constantly evolving, and New Zealand-based OM Network Corporation is at the forefront of this transformation. By integrating AI technology, specifically the 'Gemini' intelligent program generation system, they have revolutionized their approach to managing Web Application Firewalls (WAFs), which protect web applications from cyber threats. This new approach has yielded significant efficiencies, reducing manual processing times by over 90%.

Introduction to WAF

WAF, or Web Application Firewall, acts as a critical defender against cyber threats targeting web applications. Unlike traditional firewalls that safeguard the network perimeter, WAFs delve deeper by inspecting the content of communications, ensuring that malicious entities do not infiltrate secure environments. For instance, WAF systems can detect and thwart attempts to inject harmful codes through contact forms in real time, thereby serving as indispensable guardians for businesses entrusted with sensitive customer information.

Challenges in WAF Operations

One of the core challenges in optimizing WAF operations relates to the volume and complexity of alarm logs. As security protocols demand comprehensive logging—tracking all suspicious activity—the engineers monitoring these systems face numerous burdens:

1. Quick Reactions to False Positives: High-security settings often lead to legitimate actions, such as password changes, triggering unnecessary alarms. Engineers must continually assess whether these actions are threats or harmless operations.
2. Complex Log Analysis: The logs generated are often encoded in a manner that makes them utterly incomprehensible at first glance, requiring engineers to spend substantial time deciphering the messages upon their receipt.
3. Improving Reporting Accuracy: Clients frequently expect accurate insights into their security status. Extracting relevant details from vast amounts of logs demands both speed and precision, placing immense pressure on engineering teams.

Implementing the Automated Judging System

To tackle these challenges, OM Network has employed Google Apps Script (GAS) to establish an automated judging engine that operates independently of existing WAF configurations. Utilizing Gemini, the AI-driven program helps streamline the judgment process of incoming notifications. By embedding seasoned engineers' judgment criteria into the AI framework, the company has achieved heightened efficiency in log analysis.

Key Features of the Automated System

- Advanced Decoding and Visualization: The system converts complex logs into clear, comprehensible details almost instantly, enabling swift understanding of security statuses.
- Contextual Automatic Sorting: The engine can autonomously analyze specific operations or known reconnaissance bots, effectively filtering out unnecessary alerts and concentrating on genuine threats.
- Priority Reporting for Specific Clients: For clients requiring precise security updates, relevant logs are automatically flagged, ensuring immediate notifications are dispatched to the designated personnel.

With this automated system in place, the time spent reviewing notifications has drastically diminished from nearly daily checks to rare exceptions that require human intervention. This increased productivity has bolstered the overall effectiveness of fraud prevention mechanisms without compromising security standards.

Future Prospects

This initiative has validated the feasibility of utilizing AI to automate processes without altering existing security settings. Moving forward, OM Network intends to refine the judgment logic and enhance responsiveness to unknown attack patterns. Moreover, the organization plans to extend AI support further into initial response actions following detection, not simply stopping at log evaluations. By creating efficiencies through automation, OM Network envisions reallocating resources to enhance service offerings and pursue superior safety and quality standards in the industry.

Company Overview

Company Name: OM Network Corporation
Location: Niigata City, Niigata Prefecture, Japan
CEO: Shinya Yamagishi
Core Businesses: Business systems development and workforce management systems like “R-Shift”
Website: OM Network

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