OSCam with AI Fake DCW Detector Test

Overview

This repository contains a modified version of OSCam enhanced with an advanced AI-inspired Fake DCW Detection and Voting System.

The goal of this system is to improve stability and reliability when multiple Control Word (CW) sources are available, such as:

• Local readers
• CacheEx peers
• CSP sources
• Virtual readers

Instead of accepting the first CW received, this implementation collects multiple candidates and selects the most reliable one using weighted voting logic.

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🔍 Problem It Solves

In multi-reader or CacheEx environments, fake or unstable DCWs can appear.

Default behavior:

• First CW wins
• Possible glitches, freezing, or unstable decoding

With AI Fake DCW Detector:

• Multiple CWs are collected
• Sources are tracked
• Votes are counted
• Local readers can be weighted higher
• Majority or timeout logic is applied
• A reliable CW is selected

Result:

✔ Reduced fake DCWs
✔ Increased decoding stability
✔ Better CacheEx reliability
✔ Smarter CW selection

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🧠 Core Functions

1️⃣ cw_vote_add()

This function is called whenever a new CW is received.

It:

• Compares the CW with existing candidates
• Increases vote count if it matches
• Adds a new candidate if it is unique
• Tracks:
  • Total votes
  • Local votes
  • Reader source
  • CW value
• Identifies whether the source is:
  • Local reader
  • Virtual reader
  • CacheEx client
  • CSP source

Each CW candidate is stored in a voting pool.

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2️⃣ cw_vote_decide()

This function determines the final CW to use.

Decision Process

1. Count total votes
2. Verify minimum vote requirement
3. Calculate effective score:
4. Check for majority (> 50%)
5. Apply timeout logic
6. Apply fallback strategy if necessary

If a winner is found:

• CW is copied into er->cw
• CacheEx hit statistics are updated
• Optional logging is performed

If no clear winner exists, the system waits for more votes unless timeout rules apply.

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⚙ Configuration Options

Parameter	Description
cwvote_enabled	Enable/disable voting system
cwvote_max_candidates	Maximum CW candidates stored
cwvote_compare_len	Number of bytes used for CW comparison
cwvote_local_weight	Weight multiplier for local votes
cwvote_min_votes	Minimum required votes before decision
cwvote_timeout	Timeout in milliseconds
cwvote_fallback	Fallback mode (1 = best candidate, 2 = first candidate)
cwvote_log_enabled	Enable detailed debug logging

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🏆 Winner Selection Logic

A CW is selected if:

• It has a strict majority (> 50%)
  OR
• Timeout is reached and fallback mode allows selection

If timeout occurs and:

• fallback = 1 → best scoring candidate is selected
• fallback = 2 → first candidate (slot 0) is selected

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📊 Intelligent Source Awareness

The system distinguishes between:

• Trusted local readers
• Virtual readers
• CacheEx clients
• CSP sources

Local readers can be weighted higher using cwvote_local_weight, improving reliability in hybrid environments.

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📈 CacheEx Integration

If the winning CW originates from CacheEx:

• cwcacheexhit counters are incremented
• Client and account statistics are updated
• Global hit statistics are updated

This improves monitoring accuracy and performance analysis.

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🚀 Advantages

• Detects and filters fake DCWs
• Improves stability in multi-reader setups
• Reduces glitching and freezing
• Configurable and flexible logic
• Seamlessly integrated into OSCam core

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🧩 AI Concept

Although not based on machine learning, this system applies AI-style decision logic:

• Aggregates multiple inputs
• Applies weighted scoring
• Uses majority validation
• Implements adaptive timeout fallback

It behaves like deterministic intelligence for CW selection.

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Intended Use

Designed for:

• Emulated environments
• CacheEx-heavy setups
• Multi-reader configurations
• Advanced OSCam tuning
• High-stability streaming environments

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License

Based on the OSCam open-source project.
This repository includes custom modifications implementing advanced CW voting and fake DCW detection logic.