AI Auditing
AI Auditing Server Configuration
This article details the server configuration for the AI Auditing system, a critical component for maintaining data integrity and identifying potential security vulnerabilities within our MediaWiki environment. This guide is aimed at newcomers to the server administration team and provides a comprehensive overview of the necessary hardware, software, and configuration steps. Understanding this system is vital for ensuring the long-term health and security of our wiki. Please review the related articles on Server Security, Database Maintenance, and Performance Monitoring before proceeding.
Overview
The AI Auditing system utilizes machine learning algorithms to analyze server logs, database queries, and user activity for anomalous patterns. These patterns may indicate security breaches, malicious activity, or performance bottlenecks. The system operates independently of the primary MediaWiki servers to avoid impacting production performance. It receives data via secure channels and provides reports through a dedicated web interface accessible only to authorized personnel. The system integrates with our existing Incident Response Plan and Security Policies.
Hardware Requirements
The AI Auditing server requires substantial computational resources due to the demands of machine learning. The following table outlines the minimum and recommended hardware specifications:
| Component | Minimum Specification | Recommended Specification |
|---|---|---|
| Processor | Intel Xeon E5-2650 v4 (10 cores) | Intel Xeon Platinum 8280 (28 cores) |
| RAM | 64 GB DDR4 ECC | 128 GB DDR4 ECC |
| Storage (OS) | 500 GB SSD | 1 TB NVMe SSD |
| Storage (Data) | 4 TB HDD (RAID 1) | 8 TB HDD (RAID 5 or 10) |
| Network Interface | 1 Gbps Ethernet | 10 Gbps Ethernet |
These specifications are based on anticipated data volumes and processing requirements. The Network Infrastructure must be capable of handling the data transfer rates. Regularly review Hardware Monitoring to ensure optimal performance.
Software Stack
The AI Auditing system utilizes a specific software stack optimized for machine learning and data analysis. All software must be kept up-to-date with the latest security patches. See Software Updates for procedures.
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Base operating system |
| Python | 3.10 | Primary scripting language for AI models |
| TensorFlow | 2.12 | Machine learning framework |
| PostgreSQL | 14 | Database for storing audit data and model outputs |
| Nginx | 1.23 | Web server for the audit report interface |
| Fail2ban | 0.11 | Intrusion prevention framework |
The specific versions are crucial for compatibility and stability. Consult the Software Compatibility Matrix for detailed information. The Database Schema should be documented meticulously.
Configuration Details
Several configuration steps are required to ensure the AI Auditing system functions correctly and securely.
Data Ingestion
Data from the MediaWiki servers is ingested using a secure log forwarding mechanism (rsyslog with TLS encryption). The logs are then parsed and stored in the PostgreSQL database. Configuration files for rsyslog are located in `/etc/rsyslog.conf` and `/etc/rsyslog.d/`. Ensure proper Log Rotation is configured to prevent disk space exhaustion.
Machine Learning Models
The core of the AI Auditing system lies in its machine learning models. These models are trained on historical data to identify anomalous patterns. Model training is performed on a separate, dedicated server to avoid impacting the audit server's performance. The trained models are then deployed to the audit server. See Model Training Procedures for details.
Security Considerations
Security is paramount. The AI Auditing server must be isolated from the public internet. Access should be restricted to authorized personnel only via SSH with key-based authentication and a strong firewall. Regular Security Audits are essential.
| Security Measure | Description | Status |
|---|---|---|
| Firewall | UFW configured to allow only necessary traffic. | Active |
| SSH Access | Key-based authentication only, password authentication disabled. | Active |
| TLS Encryption | All data transmission is encrypted using TLS. | Active |
| Intrusion Detection | Fail2ban configured to block malicious IPs. | Active |
Access Control
Access to the web interface is controlled via Nginx authentication. User accounts are managed separately from the MediaWiki user database. Strong passwords and multi-factor authentication are required. Refer to the Access Control Policy for more details.
Monitoring and Maintenance
Regular monitoring and maintenance are essential for ensuring the AI Auditing system remains operational and effective. This includes monitoring server resource utilization, database performance, and the accuracy of the machine learning models. See System Monitoring for tools and procedures. Regularly review Error Logs for any issues.
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️