Implement TLS Matcher Quality and Confidence Scoring

[biandratti]

Objective

Implement quality scoring system for TLS fingerprint matching to provide confidence levels in device/application identification.

Requirements

• Exact match scoring (100% confidence)
• Partial match algorithms
• Fuzzy matching for similar fingerprints
• Age-based quality degradation
• Statistical confidence calculations
• Match quality metrics

Matching Algorithms

pub enum MatchQuality {
    Exact(f64),           // 1.0 = perfect match
    Partial(f64),         // 0.7-0.99 = good match  
    Fuzzy(f64),          // 0.5-0.69 = possible match
    NoMatch,             // < 0.5 = no reliable match
}

pub struct TlsMatchResult {
    pub device: String,
    pub confidence: f64,
    pub quality: MatchQuality,
    pub match_reason: String,
}

Quality Factors

• JA4 hash exact match
• Cipher suite similarity
• Extension pattern matching
• TLS version compatibility
• Database entry freshness
• Historical accuracy

Acceptance Criteria

• Quality scoring algorithm implemented
• Confidence thresholds configurable
• Match explanations provided
• Comprehensive test coverage