Tampering Plugin

Description

⚠️ Development Preview - This plugin is currently in early development.

Tampering is a security-focused plugin for CVEDIA-RT designed to provide comprehensive video tampering detection capabilities. It monitors video streams for signs of tampering, interference, or malicious manipulation, ensuring the integrity and authenticity of video surveillance systems.

This plugin is built on advanced computer vision algorithms and leverages motion detection techniques to identify various forms of video tampering, including camera obstruction, video feed manipulation, signal interference, and unauthorized modifications to the video stream.

⚠️ Development Status: This plugin is currently under active development. The core tampering detection algorithms and full API are not yet implemented. The current version provides basic infrastructure and motion-based detection capabilities as a foundation for future tampering detection features.

Key Features (Planned)

• Video Integrity Monitoring: Continuous monitoring of video stream integrity and authenticity
• Multi-Type Tampering Detection: Detection of various tampering methods including:
• Camera obstruction or blocking
• Video signal interference
• Feed manipulation or substitution
• Lens covering or defocusing
• Lighting manipulation
• Digital video alteration
• Real-Time Processing: Immediate detection and alerting of tampering attempts
• Configurable Sensitivity: Adjustable detection thresholds for different security requirements
• Security Integration: Integration with security management systems and alert mechanisms
• Forensic Analysis: Detailed logging and analysis capabilities for security investigations
• Motion-Based Foundation: Built upon robust motion detection algorithms for baseline analysis

Use Cases

• High-Security Surveillance: Critical infrastructure and sensitive area monitoring
• Forensic Video Analysis: Evidence integrity verification for legal proceedings
• Automated Security Systems: Unmanned security installations requiring tamper detection
• Compliance Monitoring: Regulatory compliance for industries requiring video integrity
• Asset Protection: Monitoring of valuable assets with tamper-evident video systems
• Perimeter Security: Detection of attempts to disable or manipulate perimeter cameras

Requirements

Hardware Requirements

• CPU: Multi-core processor (Intel/AMD x64 or ARM64)
• Memory: Minimum 2GB RAM (4GB+ recommended for high-resolution processing)
• GPU: Optional GPU acceleration for advanced video analysis
• Storage: Sufficient space for security logs and forensic data

Software Dependencies

• OpenCV: Computer vision library for video analysis algorithms
• RTCORE: CVEDIA-RT core library for plugin infrastructure
• Motion Detection: Built upon motion detection algorithms and infrastructure
• Security Libraries: Cryptographic libraries for integrity verification
• Threading Library: Multi-threading support for real-time processing

Platform Requirements

• Linux: Primary supported platform for security applications
• Kernel: Modern Linux kernel with video processing and security capabilities
• Drivers: Appropriate video input drivers and hardware acceleration drivers
• Security Framework: Integration with system security frameworks

Configuration

Basic Configuration (Development)

{
  "tampering": {
    "enabled": true,
    "sensitivity": "medium",
    "detection_methods": ["motion_based", "statistical"],
    "alert_threshold": 0.7,
    "monitoring_mode": "continuous",
    "log_level": "warning"
  }
}

Advanced Configuration (Planned)

{
  "tampering": {
    "enabled": true,
    "sensitivity": "high",
    "detection_methods": [
      "motion_based",
      "statistical_analysis", 
      "temporal_consistency",
      "spatial_analysis",
      "frequency_domain"
    ],
    "thresholds": {
      "obstruction_threshold": 0.8,
      "interference_threshold": 0.6,
      "manipulation_threshold": 0.7,
      "lighting_threshold": 0.5
    },
    "monitoring": {
      "mode": "continuous",
      "sampling_rate": 30,
      "history_window": 300,
      "baseline_update_interval": 3600
    },
    "alerts": {
      "immediate_alert": true,
      "alert_cooldown": 30,
      "severity_levels": ["low", "medium", "high", "critical"],
      "notification_methods": ["log", "webhook", "email"]
    },
    "security": {
      "integrity_verification": true,
      "encrypted_logs": true,
      "secure_timestamps": true,
      "chain_of_custody": true
    }
  }
}

Configuration Schema (Planned)

Parameter	Type	Default	Description
enabled	bool	true	Enable tampering detection
sensitivity	string	"medium"	Detection sensitivity level ("low", "medium", "high")
detection_methods	array	["motion_based"]	List of detection algorithms to use
alert_threshold	float	0.7	Threshold for triggering tampering alerts (0.0-1.0)
monitoring_mode	string	"continuous"	Monitoring mode ("continuous", "periodic", "triggered")
obstruction_threshold	float	0.8	Camera obstruction detection threshold
interference_threshold	float	0.6	Signal interference detection threshold
manipulation_threshold	float	0.7	Video manipulation detection threshold
lighting_threshold	float	0.5	Lighting tampering detection threshold
sampling_rate	int	30	Frames per second for analysis
history_window	int	300	Analysis window size in seconds
baseline_update_interval	int	3600	Baseline model update interval in seconds
immediate_alert	bool	true	Generate immediate alerts for tampering
alert_cooldown	int	30	Cooldown period between alerts in seconds
integrity_verification	bool	true	Enable video integrity verification
encrypted_logs	bool	false	Encrypt security logs
secure_timestamps	bool	true	Use secure timestamping

API Reference

C++ API (TamperingManagedImpl)

⚠️ Development Status: The full API is currently under development. The current implementation provides basic infrastructure.

Current Implementation

class TamperingManagedImpl : public iface::Tampering {
public:
    // Basic plugin lifecycle
    TamperingManagedImpl(std::string const& moduleName);
    void initialize() override;

    // Configuration management
    std::map<std::string, std::shared_ptr<ConfigDescriptor>> getConfigDescriptors() const override;

private:
    // Internal motion detection core (current implementation)
    std::unique_ptr<MotionCore> motion_;

    // Configuration handling
    expected<void> readConfig();
};

Planned API Methods

class TamperingManagedImpl : public iface::Tampering {
public:
    // Core tampering detection methods
    expected<TamperingResult> detectTampering(cbuffer frame) override;
    expected<std::vector<TamperingEvent>> getTamperingEvents() override;
    expected<TamperingStatus> getSystemStatus() override;

    // Detection method configuration
    expected<void> enableDetectionMethod(TamperingMethod method) override;
    expected<void> disableDetectionMethod(TamperingMethod method) override;
    expected<std::vector<TamperingMethod>> getActiveDetectionMethods() override;

    // Threshold and sensitivity management
    expected<void> setDetectionThreshold(TamperingType type, float threshold) override;
    expected<float> getDetectionThreshold(TamperingType type) override;
    expected<void> setSensitivityLevel(SensitivityLevel level) override;

    // Baseline and calibration
    expected<void> establishBaseline() override;
    expected<void> updateBaseline() override;
    expected<BaselineStatus> getBaselineStatus() override;

    // Alert and notification management
    expected<void> configureAlerts(AlertConfiguration config) override;
    expected<std::vector<TamperingAlert>> getPendingAlerts() override;
    expected<void> acknowledgeAlert(int alertId) override;

    // Security and forensics
    expected<SecurityReport> generateSecurityReport(TimeRange range) override;
    expected<void> enableIntegrityVerification(bool enabled) override;
    expected<IntegrityStatus> verifyVideoIntegrity(cbuffer frame) override;

    // Debug and diagnostics
    expected<DiagnosticInfo> getDiagnostics() override;
    expected<cbuffer> getAnalysisFrame() override;
    expected<TamperingStatistics> getStatistics() override;
};

Planned Data Structures

// Tampering detection result
struct TamperingResult {
    bool tamperingDetected;
    std::vector<TamperingType> detectedTypes;
    float confidence;
    cv::Rect affectedArea;
    std::chrono::system_clock::time_point timestamp;
    std::string description;
};

// Types of tampering
enum class TamperingType {
    CameraObstruction,
    SignalInterference, 
    VideoManipulation,
    LensDefocusing,
    LightingManipulation,
    DigitalAlteration,
    FeedSubstitution,
    Unknown
};

// Detection methods
enum class TamperingMethod {
    MotionBased,
    StatisticalAnalysis,
    TemporalConsistency,
    SpatialAnalysis,
    FrequencyDomain,
    MachineLearning
};

// Tampering event record
struct TamperingEvent {
    int eventId;
    TamperingType type;
    TamperingMethod detectionMethod;
    float confidence;
    cv::Rect location;
    std::chrono::system_clock::time_point startTime;
    std::chrono::system_clock::time_point endTime;
    std::string forensicHash;
    bool verified;
};

Lua API (Planned)

Tampering Detection Setup

-- Create tampering detection instance (when available)
local tampering = api.factory.tampering.create(instance, "security_tampering")

-- Configure tampering detection
tampering:configure({
    sensitivity = "high",
    detection_methods = {"motion_based", "statistical_analysis"},
    alert_threshold = 0.8,
    monitoring_mode = "continuous"
})

-- Initialize tampering detection
local success = tampering:initialize()
if success then
    api.logging.LogInfo("Tampering detection initialized successfully")
else
    api.logging.LogError("Failed to initialize tampering detection")
end

Tampering Processing

-- Process frame for tampering detection
function processTamperingFrame(frame)
    local result = tampering:detectTampering(frame)

    if result and result.tamperingDetected then
        api.logging.LogWarning("TAMPERING DETECTED!")
        api.logging.LogWarning("  Confidence: " .. result.confidence)
        api.logging.LogWarning("  Types: " .. table.concat(result.detectedTypes, ", "))
        api.logging.LogWarning(string.format("  Affected Area: %d,%d,%d,%d", 
              result.affectedArea.x, result.affectedArea.y,
              result.affectedArea.w, result.affectedArea.h))
        api.logging.LogWarning("  Timestamp: " .. result.timestamp)

        -- Handle tampering event
        handleTamperingEvent(result)

        return result
    end

    return nil
end

-- Handle tampering event
function handleTamperingEvent(tamperingResult)
    -- Log security event
    api.logging.LogError("SECURITY ALERT - TAMPERING DETECTED: " .. tamperingResult.description)

    -- Generate alert
    local alert = {
        type = "video_tampering",
        severity = "critical",
        confidence = tamperingResult.confidence,
        location = tamperingResult.affectedArea,
        timestamp = tamperingResult.timestamp,
        description = tamperingResult.description
    }

    -- Send immediate notification
    api.alerts.sendImmediate(alert)

    -- Trigger security protocols
    triggerSecurityProtocols(tamperingResult)
end

Examples

Basic Security Monitoring System (Conceptual)

// Conceptual implementation - not yet available
#include "tamperingmanaged.h"
#include "rtcore.h"

// Security monitoring system with tampering detection
class SecurityMonitoringSystem {
public:
    void initialize() {
        // Create tampering detector (when available)
        tampering_ = std::unique_ptr<TamperingManaged>(
            static_cast<TamperingManaged*>(
                TamperingManaged::create("security_monitor").release()
            )
        );

        // Configure for high-security environment
        auto config = CValue::create();
        config->set("sensitivity", "high");
        config->set("detection_methods", std::vector<std::string>{
            "motion_based", "statistical_analysis", "temporal_consistency"
        });
        config->set("alert_threshold", 0.8);
        config->set("immediate_alert", true);
        config->set("integrity_verification", true);

        tampering_->setConfig(config);

        // Initialize tampering detection
        auto result = tampering_->initialize();
        if (!result) {
            LOGE << "Failed to initialize tampering detection: " << result.error().message();
            return;
        }

        // Establish baseline
        tampering_->establishBaseline();

        LOGI << "Security monitoring system initialized";
    }

    void processSecurityFrame(const cbuffer& frame) {
        // Detect tampering (when available)
        auto tamperingResult = tampering_->detectTampering(frame);
        if (!tamperingResult) {
            LOGE << "Tampering detection failed: " << tamperingResult.error().message();
            return;
        }

        // Handle tampering detection
        if (tamperingResult->tamperingDetected) {
            handleTamperingDetection(tamperingResult.value());
        }

        // Verify video integrity
        auto integrityStatus = tampering_->verifyVideoIntegrity(frame);
        if (integrityStatus && !integrityStatus->isValid) {
            handleIntegrityViolation(integrityStatus.value());
        }
    }

private:
    std::unique_ptr<TamperingManaged> tampering_;

    void handleTamperingDetection(const TamperingResult& result) {
        LOGW << "SECURITY ALERT: Video tampering detected!";
        LOGW << "  Type: " << tamperingTypeToString(result.detectedTypes[0]);
        LOGW << "  Confidence: " << result.confidence;
        LOGW << "  Location: (" << result.affectedArea.x << ", " << result.affectedArea.y 
             << ") [" << result.affectedArea.width << "x" << result.affectedArea.height << "]";

        // Trigger security protocols
        triggerSecurityAlert(result);

        // Log for forensic analysis
        logForensicEvent(result);
    }

    void triggerSecurityAlert(const TamperingResult& result) {
        // Implementation for security alert system
        // - Send notifications to security personnel
        // - Activate additional recording
        // - Trigger alarm systems
        // - Log to security database
    }
};

Comprehensive Security System (Conceptual Lua Implementation)

-- Comprehensive security system with tampering detection
-- NOTE: This is a conceptual example for when the plugin is fully implemented

local tampering = nil  -- Will be available when plugin is complete
local alerts = api.factory.alerts.create(instance, "security_alerts")
local storage = api.factory.storage.create(instance, "security_storage")
local logger = api.logger

-- Security system configuration
local securityConfig = {
    tampering_sensitivity = "high",
    detection_methods = {
        "motion_based",
        "statistical_analysis", 
        "temporal_consistency",
        "spatial_analysis"
    },
    alert_thresholds = {
        obstruction = 0.8,
        interference = 0.7,
        manipulation = 0.9,
        lighting = 0.6
    },
    monitoring = {
        continuous = true,
        baseline_update_hours = 24,
        forensic_logging = true
    },
    response = {
        immediate_alert = true,
        automatic_recording = true,
        security_notification = true,
        system_lockdown = false
    }
}

-- Security statistics tracking
local securityStats = {
    tampering_events = 0,
    false_positives = 0,
    security_alerts = 0,
    system_uptime = 0,
    last_baseline_update = 0,
    integrity_violations = 0
}

-- Initialize comprehensive security system
function initializeSecuritySystem()
    logger.info("Initializing comprehensive video security system")

    -- Note: This will work when tampering plugin is complete
    -- tampering = api.factory.tampering.create(instance, "security_tampering")

    if tampering then
        -- Configure tampering detection
        tampering:configure({
            sensitivity = securityConfig.tampering_sensitivity,
            detection_methods = securityConfig.detection_methods,
            obstruction_threshold = securityConfig.alert_thresholds.obstruction,
            interference_threshold = securityConfig.alert_thresholds.interference,
            manipulation_threshold = securityConfig.alert_thresholds.manipulation,
            lighting_threshold = securityConfig.alert_thresholds.lighting,
            monitoring_mode = "continuous",
            immediate_alert = securityConfig.response.immediate_alert,
            integrity_verification = true,
            encrypted_logs = true
        })

        -- Initialize tampering detection
        local success = tampering:initialize()
        if not success then
            logger.error("Failed to initialize tampering detection")
            return false
        end

        -- Establish security baseline
        tampering:establishBaseline()
        logger.info("Security baseline established")
    else
        logger.warn("Tampering plugin not available - using motion-based fallback")
        -- Fallback to motion detection for basic security
        initializeMotionBasedSecurity()
    end

    -- Start security monitoring
    startSecurityMonitoring()

    logger.info("Security system initialized successfully")
    return true
end

-- Main security monitoring loop
function startSecurityMonitoring()
    -- Implement frame processing in main loop
    -- Process every frame or at desired interval
    -- Track last check times for periodic tasks:
    local lastHealthCheck = os.time()
    local lastBaselineUpdate = os.time()

    -- In your main processing loop:
    -- processSecurityFrame() for each frame
    -- Check elapsed time for periodic tasks
    -- if os.time() - lastHealthCheck > 300 then performSecurityHealthCheck() end
    -- if os.time() - lastBaselineUpdate > 86400 then updateSecurityBaseline() end
end

-- Process frame for security threats
function processSecurityFrame()
    local currentTime = api.system.getCurrentTime()

    -- Get current frame
    local frame = getCurrentSecurityFrame()
    if not frame then
        return
    end

    if tampering then
        -- Full tampering detection (when available)
        local tamperingResult = tampering:detectTampering(frame)
        if tamperingResult and tamperingResult.tamperingDetected then
            handleTamperingDetection(tamperingResult, currentTime)
        end

        -- Verify video integrity
        local integrityStatus = tampering:verifyVideoIntegrity(frame)
        if integrityStatus and not integrityStatus.isValid then
            handleIntegrityViolation(integrityStatus, currentTime)
        end
    else
        -- Fallback to motion-based detection
        processMotionBasedSecurity(frame, currentTime)
    end
end

-- Handle tampering detection event
function handleTamperingDetection(result, timestamp)
    securityStats.tampering_events = securityStats.tampering_events + 1

    logger.security(string.format(
        "CRITICAL SECURITY EVENT: Video tampering detected (Type: %s, Confidence: %.2f)",
        table.concat(result.detectedTypes, ", "), result.confidence
    ))

    -- Create high-priority security alert
    local securityAlert = {
        type = "video_tampering",
        severity = "critical",
        priority = "immediate",
        confidence = result.confidence,
        tampering_types = result.detectedTypes,
        affected_area = result.affectedArea,
        timestamp = timestamp,
        forensic_hash = result.forensicHash or generateForensicHash(result)
    }

    -- Trigger immediate response protocols
    triggerSecurityResponse(securityAlert)

    -- Log for forensic analysis
    logForensicEvent(securityAlert)

    -- Start emergency recording
    if securityConfig.response.automatic_recording then
        startEmergencyRecording(securityAlert)
    end
end

-- Trigger comprehensive security response
function triggerSecurityResponse(alert)
    securityStats.security_alerts = securityStats.security_alerts + 1

    -- Send immediate notifications
    alerts:sendCriticalAlert({
        message = "CRITICAL: Video tampering detected in security system",
        details = alert,
        notification_methods = {"sms", "email", "push", "webhook"},
        escalation = "immediate"
    })

    -- Activate additional security measures
    if securityConfig.response.system_lockdown then
        activateSystemLockdown(alert)
    end

    -- Notify security personnel
    notifySecurityPersonnel(alert)

    -- Update security databases
    updateSecurityDatabase(alert)

    logger.security(string.format(
        "Security response protocols activated for tampering event (ID: %s)",
        alert.forensic_hash
    ))
end

-- Perform periodic security health checks
function performSecurityHealthCheck()
    logger.info("Performing security system health check")

    if tampering then
        local diagnostics = tampering:getDiagnostics()
        if diagnostics then
            logger.info("Tampering detection system status: OPERATIONAL")
            logger.info("  Active detection methods:", #diagnostics.activeDetectionMethods)
            logger.info("  System uptime:", diagnostics.uptime, "seconds")
            logger.info("  Baseline status:", diagnostics.baselineStatus)
        else
            logger.warn("Tampering detection system diagnostics unavailable")
        end
    end

    -- Log security statistics
    logSecurityStatistics()
end

-- Log comprehensive security statistics
function logSecurityStatistics()
    logger.info("Security System Statistics:")
    logger.info("  Tampering Events:", securityStats.tampering_events)
    logger.info("  Security Alerts:", securityStats.security_alerts)
    logger.info("  Integrity Violations:", securityStats.integrity_violations)
    logger.info("  False Positives:", securityStats.false_positives)
    logger.info("  System Uptime:", securityStats.system_uptime, "hours")

    if tampering then
        local stats = tampering:getStatistics()
        if stats then
            logger.info("  Detection Accuracy:", stats.accuracy or "N/A")
            logger.info("  Processing FPS:", stats.processingFps or "N/A")
        end
    end
end

-- Initialize the security system
initializeSecuritySystem()

logger.info("Comprehensive video security system is active")

Current Implementation Status

Available Now (Development Preview)

• Basic Plugin Structure: Plugin registration and initialization framework
• Motion Detection Foundation: Core motion detection capabilities as a foundation
• Configuration Infrastructure: Basic configuration handling and validation
• Build System: CMake configuration for plugin compilation

In Development

• Core Tampering Algorithms: Advanced tampering detection algorithms
• Full API Implementation: Complete C++ and Lua API interfaces
• Multiple Detection Methods: Various tampering detection techniques
• Security Features: Integrity verification and forensic capabilities
• Alert System Integration: Complete alert and notification system

Future Enhancements

• Machine Learning Integration: AI-powered tampering detection
• Advanced Analytics: Statistical analysis and pattern recognition
• Cloud Integration: Cloud-based security monitoring and analysis
• Mobile Integration: Mobile apps for security monitoring and alerts

Development Guidelines

For developers working on completing this plugin:

Implementation Priorities

1. Core Detection Algorithms: Implement tamperingcore.cpp with actual tampering detection logic
2. Interface Definition: Create the iface::Tampering interface in the main SDK
3. Factory Registration: Add Tampering factory registration to main factory.h
4. Lua Bindings: Implement tamperinglua.cpp for scripting support
5. Configuration Schema: Define comprehensive configuration parameters
6. Testing Framework: Create unit tests and integration tests

Architecture Recommendations

• Multi-Algorithm Approach: Implement multiple detection methods for different tampering types
• Baseline Learning: Establish and maintain baseline models for normal video behavior
• Statistical Analysis: Use statistical methods to detect anomalies in video streams
• Machine Learning: Consider ML approaches for advanced tampering detection
• Performance Optimization: Ensure real-time performance for security applications

Best Practices

Security Considerations

• Integrity Verification: Implement cryptographic integrity checking for video streams
• Secure Logging: Encrypt security logs and use secure timestamps
• Chain of Custody: Maintain forensic chain of custody for evidence
• Access Control: Implement proper access controls for security functions

Performance Optimization

• Real-Time Processing: Optimize algorithms for real-time security monitoring
• Resource Management: Manage CPU and memory usage efficiently
• Scalability: Design for multiple concurrent video streams
• Hardware Acceleration: Utilize available hardware acceleration

Integration Guidelines

• Security Systems: Design for integration with existing security infrastructure
• Alert Management: Implement comprehensive alert and notification systems
• Forensic Tools: Provide tools for security investigation and analysis
• Compliance: Consider regulatory compliance requirements for security systems

Troubleshooting

Current Development Issues

Plugin Not Available

• Issue: Tampering plugin factory not found
• Cause: Plugin is incomplete and not registered in main factory
• Workaround: Use Motion Detection plugin for basic security monitoring
• Solution: Complete plugin development and factory registration

Missing Dependencies

• Issue: Build failures due to missing files
• Cause: Referenced source files (tamperingcore.cpp, tamperinglua.cpp) don't exist
• Solution: Implement missing source files or remove from CMakeLists.txt

Interface Errors

• Issue: Undefined iface::Tampering interface
• Cause: Interface not defined in main SDK
• Solution: Define interface in SDK headers and implement factory registration

Future Troubleshooting (Planned)

High False Positive Rate

• Solution: Adjust detection thresholds and improve baseline models
• Prevention: Regular baseline updates and environmental calibration

Performance Issues

• Solution: Optimize detection algorithms and use hardware acceleration
• Monitoring: Implement performance metrics and monitoring

Security Alert Fatigue

• Solution: Implement alert prioritization and cooldown mechanisms
• Management: Use statistical analysis to reduce false positives

Integration Examples

Security Management System Integration (Conceptual)

// Integration with security management systems
// NOTE: This is conceptual - actual implementation pending

class SecurityManagementIntegration {
public:
    void integrateTamperingDetection() {
        // Initialize tampering detection
        initializeTamperingSystem();

        // Setup security event handlers
        setupSecurityEventHandlers();

        // Configure alert routing
        configureAlertRouting();

        // Start monitoring
        startSecurityMonitoring();
    }

private:
    void handleSecurityEvent(const TamperingEvent& event) {
        // Route to appropriate security systems
        routeToSecuritySystems(event);

        // Update security databases
        updateSecurityRecords(event);

        // Generate compliance reports
        generateComplianceReports(event);
    }
};

See Also

• Motion Plugin - Foundation motion detection capabilities
• EventAction Plugin - Event processing and security responses
• Processing Plugins Overview - All processing plugins
• Plugin Overview - Complete plugin ecosystem
• Security Integration Guide - Security system integration patterns
• Plugin Development SDK - Guide for completing this plugin