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OSCam with AI Fake DCW Detector
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.
🔍 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
🧠 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.
2️⃣ cw_vote_decide()
This function determines the final CW to use.
Decision Process
- Count total votes
- Verify minimum vote requirement
- Calculate effective score:
- Check for majority (> 50%)
- Apply timeout logic
- 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.
⚙ 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 |
🏆 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 selectedfallback = 2→ first candidate (slot 0) is selected
📊 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.
📈 CacheEx Integration
If the winning CW originates from CacheEx:
cwcacheexhitcounters are incremented- Client and account statistics are updated
- Global hit statistics are updated
This improves monitoring accuracy and performance analysis.
🚀 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
🧩 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.
Intended Use
Designed for:
- Emulated environments
- CacheEx-heavy setups
- Multi-reader configurations
- Advanced OSCam tuning
- High-stability streaming environments
License
Based on the OSCam open-source project.
This repository includes custom modifications implementing advanced CW voting and fake DCW detection logic.