Safeguard your proprietary AI models and algorithms from theft, unauthorized use, and reverse engineering with enterprise-grade IP protection and forensic watermarking.
A single stolen model can cost companies millions in lost competitive advantage, development costs, and legal fees. Training state-of-the-art models costs $1M-$50M+, making them prime targets for industrial espionage and competitive theft.
Attackers query your API systematically to reverse-engineer model behavior and create functional copies without your knowledge.
Direct theft of model parameters through compromised infrastructure, insider threats, or supply chain vulnerabilities.
Stolen models deployed without licensing, violating IP rights and enabling competitors to bypass R&D investments.
Embed invisible, robust signatures into your models to prove ownership and trace unauthorized copies:
Prevent model extraction through API abuse with intelligent rate limiting and detection:
Strict controls to ensure only authorized parties access your models and infrastructure:
Complement technical defenses with robust legal frameworks and documentation:
When theft occurs, rapid detection and response minimize damage and enable legal recourse:
Don't risk losing millions in R&D investment. Secure your models with enterprise-grade IP protection.
Our watermarking techniques embed signatures during training that have negligible impact on accuracy (typically less than 0.1%). We use trigger-response pairs on rare inputs that don't occur in normal use, activation pattern modifications that preserve functionality, and statistical fingerprints in weight distributions. The watermarks are robust to fine-tuning, pruning, and other common model modifications, while remaining imperceptible to users and not affecting production performance.
Yes, our watermarks are specifically designed to be robust against common evasion techniques. We use distributed redundant watermarks across multiple layers, embed signatures in fundamental model behavior patterns, and employ cryptographic techniques that survive parameter modifications. Testing shows our watermarks remain detectable even after aggressive fine-tuning on new data, model pruning up to 50% of parameters, and quantization to 8-bit precision. We also implement multiple independent watermarking schemes for redundancy.
With proper IP protection in place, you have several legal options: trade secret misappropriation claims (strongest protection for model weights and architecture), copyright infringement for original training code and data, patent infringement if you've patented novel architectures or methods, and breach of contract for violations of usage agreements. Our watermarking provides forensic evidence of ownership for legal proceedings. We partner with IP law specialists who have successfully recovered damages and stopped unauthorized use in multiple jurisdictions.
We implement multi-layered API protection including adaptive rate limiting based on query patterns, prediction perturbation that adds minimal noise to prevent accurate extraction, query monitoring using ML to detect systematic extraction attempts, and honeypot techniques to identify attackers. We also implement confidence score smoothing, ensemble randomization, and input preprocessing that makes extraction prohibitively expensive while maintaining accuracy for legitimate users. Typical deployments reduce extraction success rates by over 90%.
Yes, though the approach differs from greenfield deployments. For existing models, we can add API-level protections immediately (rate limiting, query monitoring, prediction perturbation), implement access controls and authentication layers, deploy monitoring systems to detect theft attempts, and add legal protections through updated terms of service. For the strongest protection including watermarking, we can create a new version through transfer learning that maintains performance while adding embedded signatures. We design a phased migration plan to minimize disruption.
Comprehensive security for your entire machine learning infrastructure.
Protect your models from adversarial manipulation and attacks.
Ensure your AI systems meet regulatory requirements and standards.
Identify vulnerabilities and assess risks in your AI deployment.
Protect your valuable AI intellectual property with comprehensive model security and watermarking solutions from Boaweb AI.
Based in Lund, Sweden | Serving clients globally |