Security & Compliance

Overview

As an independent AI and data science consultant based in France, I am committed to maintaining the highest standards of security and compliance. This page outlines my security approach, compliance commitments, and how I work with clients to ensure data protection and regulatory compliance.

Consultant Model & Data Handling

I operate as an independent consultant, working within client-managed systems and environments. This approach ensures:

Client data remains in client-controlled systems throughout the project lifecycle
I work within client-managed cloud environments (Azure, AWS) under their accounts and security controls
Client retains full control and ownership of their data at all times
I do not maintain separate infrastructure for client data processing
I adapt my working practices to align with client security policies and requirements

Compliance & Regulatory Framework

As a France-based consultant, I am subject to and ensure compliance with:

GDPR (General Data Protection Regulation): Full compliance with EU data protection requirements
French Data Protection Laws (CNIL): Compliance with French data protection authority regulations
EU AI Act: Alignment with EU AI Act principles and requirements for responsible AI development
Client-Specific Requirements: I work with clients to ensure solutions meet their specific regulatory needs (industry-specific standards, international regulations, etc.)

Security Practices

I implement security practices appropriate to my consultant model and client requirements:

Secure Development: Secure coding practices, code reviews, and testing protocols
Access Management: Multi-factor authentication, principle of least privilege, and secure credential management for client system access
Data Minimization: Accessing only necessary data for project delivery, following data minimization principles
Secure Communication: Encrypted communication channels and secure file transfer methods
Cloud Platform Security: Leveraging enterprise-grade security features of Azure and AWS platforms (encryption, IAM, network isolation)
Data Cleanup: Secure deletion of local copies and temporary files upon project completion

Certifications & Client Environments

As an independent consultant, I work within client-certified environments rather than maintaining my own certified infrastructure:

I work within client cloud environments that maintain enterprise certifications (ISO 27001, SOC 2, etc.)
For enterprise clients requiring specific certifications, I adapt my practices to align with their certified security frameworks
I leverage cloud platforms (Azure, AWS) that maintain ISO 27001, SOC 2, and other enterprise security certifications
My academic credentials (PhD) and published peer-reviewed research demonstrate methodological rigor and quality assurance

AI Governance & Responsible AI

I maintain a comprehensive approach to AI governance, ensuring responsible development and deployment of AI solutions aligned with international frameworks and regulatory requirements.

AI Governance & Oversight

As an independent consultant, I integrate AI governance into all project phases:

Responsible AI Integration: AI ethics and governance considerations are embedded from project design through deployment
Client Collaboration: I work with clients to establish appropriate AI governance structures for their organizations
Framework Alignment: Solutions are designed to align with client governance requirements and industry standards
Continuous Review: Regular assessment of AI solutions against governance principles and regulatory requirements

Model Risk Management

I implement comprehensive model risk management practices throughout the AI lifecycle:

Model Validation: Rigorous validation using appropriate metrics, cross-validation, and holdout testing before deployment
Bias Detection & Mitigation: Systematic bias detection using fairness metrics, demographic parity analysis, and bias mitigation techniques (pre-processing, in-processing, post-processing)
Model Monitoring: Continuous monitoring of model performance, accuracy drift, and data distribution shifts in production
Explainability: Implementation of explainability techniques (SHAP, LIME, feature importance) to provide transparency in AI decision-making
Model Versioning: Comprehensive version control and audit trails for all models, including training data, hyperparameters, and performance metrics
Performance Drift Monitoring: Automated monitoring for model degradation, concept drift, and data drift with alerting mechanisms

Responsible AI Principles

I align my AI development practices with recognized responsible AI frameworks:

NIST AI Risk Management Framework (AI RMF): Following NIST AI RMF principles for mapping, measuring, and managing AI risks
OECD AI Principles: Adherence to OECD principles including inclusive growth, human-centered values, transparency, robustness, and accountability
EU AI Act Alignment: Ensuring solutions comply with EU AI Act requirements, including risk classification and conformity assessments
Fairness: Designing AI systems to avoid unfair discrimination and ensure equitable outcomes across different groups
Transparency: Providing clear explanations of AI system capabilities, limitations, and decision-making processes
Accountability: Establishing clear responsibility and oversight mechanisms for AI system outcomes
Inclusiveness: Ensuring AI solutions are designed to be accessible and beneficial to diverse user groups

Security & Privacy in AI

I implement security and privacy safeguards specific to AI systems:

Data Minimization: Collecting and processing only the minimum data necessary for model training and inference
Anonymization & Pseudonymization: Applying data anonymization and pseudonymization techniques where appropriate to protect privacy
Secure Model Deployment: Implementing secure deployment practices including model encryption, secure APIs, and access controls
Third-Party Model Assessment: Conducting risk assessments for third-party models and AI services before integration
Adversarial Robustness: Testing models for adversarial attacks and implementing robustness measures
Privacy-Preserving Techniques: Utilizing techniques such as differential privacy, federated learning, or secure multi-party computation where applicable

Regulatory Alignment

I ensure AI solutions align with applicable regulations and standards:

EU AI Act Compliance: Solutions are designed to comply with EU AI Act requirements, including risk-based classification and conformity assessments
GDPR Integration: AI systems are designed with GDPR compliance in mind, including data subject rights and privacy by design
Industry-Specific Regulations: Adapting solutions to meet industry-specific AI regulations (e.g., financial services, healthcare, etc.)
International Standards: Alignment with international AI governance standards and best practices

Client-Specific AI Controls

I work with clients to implement tailored AI governance and controls:

Customized Governance Frameworks: Developing client-specific AI governance structures aligned with their organizational needs
Regulatory Requirements: Ensuring solutions meet client-specific regulatory requirements and industry standards
Risk Appetite Alignment: Adapting AI risk management practices to match client risk tolerance and business objectives
Ongoing Support: Providing guidance on AI governance, monitoring, and continuous improvement post-deployment

Incident Response & Handling

I maintain a structured approach to incident handling aligned with recognized frameworks and best practices, adapted for my consultant model and client collaboration.

Governance & Oversight

As an independent consultant, I maintain incident response governance appropriate to my operational model:

Structured Incident Framework: Defined incident response procedures aligned with NIST SP 800-61 and ISO/IEC 27035 principles
Client Collaboration: Working within client incident response structures and coordinating with their security teams
Clear Escalation Procedures: Defined escalation paths for different incident severity levels
Documentation Standards: Maintaining incident logs, timelines, and response documentation

Detection & Monitoring

I implement detection and monitoring practices appropriate to my consultant model:

Client System Monitoring: Working within client-managed monitoring systems (SIEM, logging, alerting) when operating in their environments
Anomaly Detection: Leveraging client monitoring capabilities and AI/ML-based anomaly detection in solutions I develop
Logging & Audit Trails: Maintaining appropriate logging for my consulting activities and ensuring alignment with client logging requirements
Threat Intelligence: Staying informed about relevant threats and vulnerabilities that may affect client systems or solutions
Proactive Monitoring: Regular review of system health, model performance, and security indicators in deployed solutions

Response & Containment

I follow structured response and containment procedures:

Immediate Notification: Immediate notification to affected clients via multiple communication channels
Incident Classification: Rapid assessment and classification of incident severity and type
Containment Procedures: Following client containment protocols when working in their systems, or implementing appropriate containment for issues in solutions I've developed
Client Coordination: Coordinating with client incident response teams and following their established playbooks
Secure Communication: Using encrypted channels for incident-related communications
GDPR Compliance: Notifying affected parties within 72 hours as required by GDPR when applicable

Recovery & Review

I maintain comprehensive recovery and post-incident review processes:

Recovery Procedures: Coordinating with clients on recovery activities and system restoration
Root Cause Analysis: Conducting thorough root cause analysis to identify underlying issues and contributing factors
Post-Incident Reporting: Documenting incident details, response actions, and outcomes in post-incident reports
Lessons Learned: Identifying lessons learned and improvement opportunities from each incident
Continuous Improvement: Updating incident response procedures and practices based on lessons learned and evolving threats
Client Debriefing: Conducting debrief sessions with clients to review incident response effectiveness and identify improvements

Compliance & Standards

I align my incident handling practices with recognized frameworks and standards:

NIST SP 800-61: Following NIST Computer Security Incident Handling Guide principles for incident response lifecycle
ISO/IEC 27035: Aligning with ISO/IEC 27035 Information Security Incident Management principles and processes
MITRE ATT&CK: Utilizing MITRE ATT&CK framework for threat modeling and understanding adversary tactics and techniques
GDPR Incident Requirements: Ensuring compliance with GDPR requirements for personal data breach notification and response
Client Framework Alignment: Adapting practices to align with client-specific incident response frameworks and requirements

Client-Specific Adaptation

I work with clients to implement tailored incident handling protocols:

Custom Playbooks: Developing or adapting incident response playbooks to match client requirements and industry-specific needs
Integration with Client CSIRT: Working within client Computer Security Incident Response Teams (CSIRT) structures when available
Regulatory Alignment: Ensuring incident response procedures meet client-specific regulatory requirements (e.g., financial services, healthcare)
Industry Best Practices: Adapting incident handling to align with industry-specific best practices and standards

Business Continuity & Disaster Recovery

As an independent consultant, I maintain business continuity practices to ensure reliable service delivery and work within client-managed disaster recovery frameworks:

Personal Business Continuity

I maintain continuity practices to ensure uninterrupted consulting services:

Redundant Communication Channels: Multiple communication methods (email, phone, secure messaging) to maintain client contact
Remote Work Capability: Ability to work from multiple locations with secure access to client systems
Data Backup: Regular backup of local project files and documentation to secure cloud storage
Documentation Management: Project documentation stored in secure, accessible locations

Client System Resilience

When working within client systems, I align with their business continuity and disaster recovery frameworks:

Client BCP/DRP Alignment: I work within client-managed cloud environments (Azure, AWS) that maintain enterprise-grade redundancy, backup strategies, and failover capabilities
Cloud Platform Resilience: Leveraging cloud platforms with built-in redundancy, automated backups, multi-region availability, and disaster recovery features
Client-Specific Requirements: For regulated industries or clients with specific BCP/DRP requirements (e.g., ISO 22301, NIST SP 800-34), I adapt my practices to align with their frameworks
Recovery Objectives: I collaborate with clients to understand their Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO) and design solutions accordingly

Crisis Communication

In the event of disruptions or incidents:

Immediate notification to affected clients via multiple communication channels
Regular status updates during incident resolution
Coordination with client incident response and business continuity teams
Post-incident review and lessons learned documentation

Standards & Best Practices

I align my continuity practices with recognized standards and frameworks:

ISO 22301 Principles: Following business continuity management principles appropriate for a consultant model
NIST SP 800-34 Guidance: Applying contingency planning best practices in solution design
Cloud Platform Standards: Working within Azure and AWS environments that maintain enterprise continuity certifications
Client Framework Alignment: Adapting to client-specific BCP/DRP frameworks and requirements

Important Note: As a consultant working within client-managed systems, the primary BCP/DRP responsibility lies with the client for their infrastructure and data. I ensure continuity of my consulting services and align with client continuity frameworks.

Subprocessors

The following third-party services are used for my business operations (client project data is processed within client-managed systems):

Email Service Provider: For client communications (data processed in EU/France)
Google Analytics: Website analytics with IP anonymization enabled (GDPR-compliant configuration)
Cloud Platforms (Azure/AWS): When working in client systems, data is processed within client-managed accounts and environments

Important Note: Client project data is processed exclusively within client-managed cloud environments under their accounts and security controls. I do not maintain separate infrastructure for client data processing.

Security Contact

For security-related inquiries or to report a security concern, please contact:

Email: e.guliyev@caspiananalytics.fr

Location: Lille, France