AI Security Services - AI Cybersecurity
Secure your AI implementations with NOXMON's comprehensive cybersecurity strategies designed for artificial intelligence and machine learning systems. We address unique AI risks including prompt injection attacks, model poisoning, and adversarial machine learning threats.
Secure AI Implementation
NOXMON's AI cybersecurity services address the unique security challenges posed by artificial intelligence and machine learning systems. Our expert team provides comprehensive security assessments for AI implementations, including prompt engineering security, LLM vulnerability testing, and AI model hardening.
We develop secure AI governance frameworks that implement responsible AI practices while establishing robust monitoring systems for AI-powered applications. Our approach covers the entire AI lifecycle, from data preparation and model training to deployment and ongoing operations.
From AI red teaming and adversarial testing to secure MLOps pipelines and AI ethics compliance, NOXMON ensures your artificial intelligence initiatives are protected against emerging threats while maintaining operational efficiency and regulatory compliance.
AI Security Threat Landscape
AI-Specific Threats
- Prompt Injection Attacks. Malicious prompts designed to manipulate AI model behavior and bypass safety measures
- Model Poisoning. Attacks targeting training data to compromise model integrity and performance
- Adversarial Examples. Crafted inputs designed to fool AI models into making incorrect predictions
- Data Exfiltration. Unauthorized extraction of sensitive training data through model interrogation
Emerging AI Risks
- Model Inversion Attacks. Reconstruction of training data from model parameters and outputs
- Membership Inference. Determining if specific data was used in model training
- AI Supply Chain Attacks. Compromised AI models, datasets, or development tools
- Deepfake Generation. Creation of synthetic media for disinformation and fraud
Our AI Cybersecurity Services
AI Security Assessment
- Prompt Engineering Security. Assessment and hardening of prompt injection vulnerabilities in LLMs
- LLM Vulnerability Testing. Comprehensive security testing of large language models and applications
- AI Model Security Audit. Deep security analysis of machine learning models and algorithms
- Data Pipeline Security. Security assessment of AI training and inference data pipelines
AI Risk Management
- AI Governance Framework. Development of comprehensive AI governance and risk management policies
- Responsible AI Implementation. Ethical AI deployment with bias detection and fairness testing
- AI Risk Assessment. Quantitative and qualitative assessment of AI-related risks
- AI Compliance Management. Ensuring compliance with AI regulations and industry standards
Secure AI Development Lifecycle
1. Data Security
Secure data collection, validation, and preprocessing with privacy protection measures.
2. Model Security
Secure model development with adversarial training and robustness testing.
3. Testing & Validation
Comprehensive security testing including red teaming and vulnerability assessment.
4. Secure Deployment
Secure MLOps practices with encrypted model deployment and access controls.
5. Monitoring
Continuous monitoring for anomalies, attacks, and model performance degradation.
AI Security Best Practices
Technical Controls
- Input Validation & Sanitization. Robust input filtering and validation to prevent injection attacks
- Model Encryption & Protection. Encryption of model parameters and intellectual property protection
- Differential Privacy. Privacy-preserving techniques to protect training data confidentiality
- Adversarial Training. Training models to be robust against adversarial examples
Operational Security
- AI Access Controls. Role-based access control for AI systems and model management
- Audit Logging. Comprehensive logging of AI system interactions and decisions
- Model Versioning. Secure model version control and rollback capabilities
- Incident Response. AI-specific incident response procedures and forensic capabilities
AI Regulatory Compliance
Global AI Regulations
- EU AI Act. Compliance with European Union AI regulation requirements
- GDPR & AI. Privacy compliance for AI systems processing personal data
- US AI Executive Order. Federal AI safety and security requirements
Industry Standards
- NIST AI Risk Management. Implementation of NIST AI RMF guidelines
- ISO/IEC 23053. AI risk management framework compliance
- IEEE AI Standards. Ethical design and algorithmic bias standards
Sector-Specific Requirements
- Financial Services. Model risk management and algorithmic accountability
- Healthcare AI. FDA AI/ML guidance and medical device requirements
- Government Contracts. Federal AI security and trustworthiness requirements
Why Choose NOXMON for AI Cybersecurity
NOXMON combines deep cybersecurity expertise with cutting-edge AI security knowledge to provide comprehensive protection for your artificial intelligence initiatives. Our team includes AI security researchers, machine learning engineers, and cybersecurity professionals who understand both the technical and business aspects of AI security.
We stay at the forefront of AI security research, continuously updating our methodologies to address emerging threats and vulnerabilities. Our approach balances security requirements with business needs, ensuring your AI systems are both secure and functional.
Partner with NOXMON to build AI systems that are secure by design, compliant with evolving regulations, and resilient against both current and future threats. Our comprehensive AI cybersecurity services enable you to harness the power of artificial intelligence while maintaining the highest security standards.
Tell us about your project
Our offices
- Houghton
101 W. Lakeshore Dr.
Houghton, MI 49931
(212) 913-9184
info@noxmon.com - New York City
34 West 13th Street
New York, NY 10011
(212) 913-9184
info@noxmon.com