One AntiCheat 图标

One AntiCheat

作者:rebot | 分类:模组

价格:0 墨喵币 下载量:0 点赞:0 版本 4
本资源为搬运资源,原资源地址: https://modrinth.com/mod/one-anticheat
资源信息

Minecraft 版本: 1.8 1.8.1 1.8.2 1.8.3 1.8.4 1.8.5 1.8.6 1.8.7 1.8.8 1.8.9 1.9 1.9.1 1.9.2 1.9.3 1.9.4 1.10 1.10.1 1.10.2 1.11 1.11.1 1.11.2 1.12 1.12.1 1.12.2 1.13 1.13.1 1.13.2 1.14 1.14.1 1.14.2 1.14.3 1.14.4 1.15 1.15.1 1.15.2 1.16 1.16.1 1.16.2 1.16.3 1.16.4 1.16.5 1.17 1.17.1 1.18 1.18.1 1.18.2 1.19 1.19.1 1.19.2 1.19.3 1.19.4 1.20 1.20.1 1.20.2 1.20.3 1.20.4 1.20.5 1.20.6 1.21 1.21.1 1.21.2 1.21.3 1.21.4 1.21.5 1.21.6 1.21.7 1.21.8

平台: paper spigot

标签: optimization technology utility

资源介绍

BIG UPDATE COMING V1.2.1 WILL BE BETTER

Server Hosting I use daily to test is https://witherhosting.com/

?️ Advanced AI Anti-Cheat System for Minecraft 1.8-1.21.8

AntiSystem v1.2.0 is a next-generation, AI-powered anti-cheat plugin featuring advanced machine learning detection engines, deep neural networks, and intelligent behavioral analysis. Designed for maximum protection with zero false positives across all supported Minecraft versions.

? Advanced Detection Capabilities

Movement Analysis: Flight, speed, reach, teleportation, and sophisticated movement pattern detection
Combat Intelligence: Kill aura, auto-clicker, reach hacks, and combat automation prevention
Behavioral AI: Deep learning behavioral analysis with adaptive pattern recognition
Inventory Protection: Advanced inventory exploit detection and item duplication prevention
Cross-Platform: Seamless Java and Bedrock player support with platform-specific optimizations
Bypass Prevention: ML-powered detection of sophisticated cheat bypasses and obfuscation

? Machine Learning Engine

Deep Neural Networks: Multi-layer perceptron with advanced feature extraction
Ensemble Learning: Combines multiple ML models for superior accuracy
Anomaly Detection: Isolation Forest algorithm for detecting unusual behavior patterns
Gradient Boosting: Advanced ensemble method for high-precision classification
Adaptive Decision Trees: Self-optimizing decision trees that learn from server data
Real-time Learning: Continuous model updates based on live player behavior

? Enhanced Staff Tools

ML-Powered Analytics: Advanced staff monitoring with AI-driven insights
Smart Alert System: Intelligent violation notifications with confidence scoring
Performance Dashboards: Real-time server performance and detection metrics
Behavioral Insights: Deep analysis of player patterns and anomaly detection
Clean Console Output: Spam-free logging with intelligent message filtering

? Revolutionary Features

Intelligent Configuration: Manual configuration with ML-optimized default settings
Zero False Positives: AI-trained thresholds eliminate innocent player punishment
Performance Optimized: Advanced resource management with minimal server impact
Cross-Platform Excellence: Full Java and Bedrock compatibility with touch/controller detection
Database Flexibility: SQLite (default) and MySQL support with automatic optimization
Version Compatibility: Full support for Minecraft 1.8 through 1.21.8

? Configuration Structure

The plugin uses 5 optimized configuration files:
config.yml: Core settings with advanced ML configurations
bedrockac.yml: Bedrock-specific detection with touch/controller AI
staff.yml: Staff management with ML-enhanced analytics
reasons.yml: AI-powered violation categorization with smart recommendations
plugin.yml: Plugin metadata and command definitions

⚙️ System Requirements

Server: Spigot/Paper 1.8-1.21.8 (or compatible forks)
Java: Version 8 or higher
Memory: Minimum 512MB allocated for ML processing
Optional: Geyser/Floodgate for enhanced Bedrock support
Database: SQLite (included) or MySQL for large networks

? Recent Updates (v1.2.0)

• Extended Minecraft version support up to 1.21.8
• Implemented advanced deep neural network detection
• Added ensemble learning models for improved accuracy
• Enhanced Bedrock player detection with touch/controller AI
• Streamlined configuration from 6 files to 5 optimized files
• Improved ML feature distribution across configuration files
• Enhanced staff analytics with behavioral insights
• Optimized performance for large server networks

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