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@iota-big3/sdk-security

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Advanced security features including zero trust, quantum-safe crypto, and ML threat detection

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/** * ML-Based Threat Detection * Uses machine learning for advanced threat detection */ import { EventEmitter } from 'events'; export interface ThreatDetectorConfig { modelPath?: string; sensitivity: 'low' | 'medium' | 'high'; realtimeAnalysis: boolean; anomalyThreshold: number; } export interface ThreatEvent { id: string; type: ThreatType; severity: 'low' | 'medium' | 'high' | 'critical'; confidence: number; source: string; timestamp: Date; indicators: string[]; recommendation: string; } export declare enum ThreatType { SQL_INJECTION = "sql_injection", XSS = "xss", BRUTE_FORCE = "brute_force", ANOMALOUS_BEHAVIOR = "anomalous_behavior", DATA_EXFILTRATION = "data_exfiltration", PRIVILEGE_ESCALATION = "privilege_escalation", MALWARE = "malware", DDoS = "ddos" } export declare class MLThreatDetector extends EventEmitter { private model?; private config; private behaviorBaseline; constructor(_config: ThreatDetectorConfig); initialize(): Promise<void>; /** * Analyze request for threats */ analyzeRequest(request: { method: string; path: string; headers: Record<string, string>; body?: unknown; ip: string; userId?: string; }): Promise<ThreatEvent[]>; /** * Extract features for ML model */ private extractFeatures; /** * ML prediction */ private predict; /** * Rule-based threat detection */ private runRuleBasedChecks; /** * Behavioral analysis using UEBA */ private analyzeBehavior; /** * Create default ML model */ private createDefaultModel; /** * Helper methods */ private createThreat; private generateThreatId; private encodeMethod; private countSuspiciousPatterns; private calculateEntropy; private indexToThreatType; private extractIndicators; private calculateSeverity; private getRecommendation; private createBehaviorProfile; } //# sourceMappingURL=ml-threat-detector.d.ts.map