Security Analytics and Intelligence
Security Analytics and Intelligence
Advanced analytics help identify threats that simple rule-based systems might miss.
// Security analytics platform
class SecurityAnalyticsPlatform {
// Machine learning-based threat detection
class MLThreatDetector {
private val models = mapOf(
"anomaly_detection" to loadAnomalyDetectionModel(),
"threat_classification" to loadThreatClassificationModel(),
"risk_scoring" to loadRiskScoringModel()
)
fun analyzeSecurityEvents(events: List<SecurityEvent>): ThreatAnalysis {
// Feature extraction
val features = FeatureExtractor.extract(events)
// Anomaly detection
val anomalies = models["anomaly_detection"]?.predict(features)
?.filter { it.anomalyScore > 0.8 }
?: emptyList()
// Threat classification
val threats = anomalies.mapNotNull { anomaly ->
models["threat_classification"]?.classify(anomaly)
}
// Risk scoring
val riskScore = models["risk_scoring"]?.calculateRisk(
threats = threats,
context = SecurityContext.current()
) ?: 0.0
return ThreatAnalysis(
anomalies = anomalies,
threats = threats,
riskScore = riskScore,
recommendations = generateRecommendations(threats, riskScore)
)
}
// Continuous model improvement
fun updateModels(feedback: SecurityFeedback) {
scope.launch {
// Retrain models with new data
val updatedModels = ModelTrainer.retrain(
currentModels = models,
newData = feedback.labeledEvents,
hyperparameters = optimizeHyperparameters()
)
// Validate before deployment
if (validateModels(updatedModels)) {
deployModels(updatedModels)
}
}
}
}
// Threat intelligence integration
class ThreatIntelligenceHub {
private val threatFeeds = listOf(
OWASPThreatFeed(),
CommercialThreatFeed(),
OpenSourceIntelligence(),
InternalThreatDatabase()
)
suspend fun enrichSecurityEvent(event: SecurityEvent): EnrichedSecurityEvent {
val enrichments = coroutineScope {
threatFeeds.map { feed ->
async {
feed.lookup(event)
}
}.awaitAll()
}
return EnrichedSecurityEvent(
originalEvent = event,
threatIntel = enrichments.filterNotNull(),
riskScore = calculateEnrichedRisk(event, enrichments),
indicators = extractIndicators(enrichments)
)
}
fun checkIOCs(indicators: List<Indicator>): List<ThreatMatch> {
val matches = mutableListOf<ThreatMatch>()
indicators.forEach { indicator ->
threatFeeds.forEach { feed ->
feed.checkIOC(indicator)?.let { match ->
matches.add(match)
}
}
}
return matches
}
}
// Security metrics and KPIs
class SecurityMetricsCollector {
fun calculateSecurityMetrics(): SecurityMetrics {
return SecurityMetrics(
mttr = calculateMeanTimeToRespond(),
mttd = calculateMeanTimeToDetect(),
falsePositiveRate = calculateFalsePositiveRate(),
incidentCount = getIncidentCount(),
severityDistribution = getSeverityDistribution(),
topThreats = getTopThreats(),
complianceScore = calculateComplianceScore()
)
}
private fun calculateMeanTimeToRespond(): Duration {
val incidents = IncidentDatabase.getResolvedIncidents(
TimeRange.last30Days()
)
val responseTimes = incidents.map { incident ->
incident.resolvedAt - incident.detectedAt
}
return if (responseTimes.isNotEmpty()) {
Duration.ofMillis(responseTimes.average().toLong())
} else {
Duration.ZERO
}
}
fun generateExecutiveDashboard(): Dashboard {
val metrics = calculateSecurityMetrics()
return Dashboard(
widgets = listOf(
MetricWidget(
title = "Security Score",
value = calculateOverallSecurityScore(),
trend = calculateTrend(Period.WEEK)
),
ChartWidget(
title = "Incident Trend",
data = getIncidentTrend(Period.MONTH),
type = ChartType.LINE
),
TableWidget(
title = "Top Threats",
headers = listOf("Threat", "Count", "Severity"),
rows = metrics.topThreats.map { threat ->
listOf(threat.name, threat.count.toString(), threat.severity)
}
),
HeatmapWidget(
title = "Attack Geography",
data = getAttackGeography()
)
)
)
}
}
}