HiddenLayer, a Gartner recognized Cool Vendor for AI Security, is the leading provider of Security for AI. Its security platform helps enterprises safeguard the machine learning models behind their most important products. HiddenLayer is the only company to offer turnkey security for AI that does not add unnecessary complexity to models and does not require access to raw data and algorithms. Founded by a team with deep roots in security and ML, HiddenLayer aims to protect enterprise’s AI from inference, bypass, extraction attacks, and model theft. The company is backed by a group of strategic investors, including M12, Microsoft’s Venture Fund, Moore Strategic Ventures, Booz Allen Ventures, IBM Ventures, and Capital One Ventures.
The Challenges
Adapting to AI
Public sector operations are dynamic and are characterized by complex challenges. Protecting sensitive data from exposure and manipulation is critical as threats to AI evolve. Additionally, the high costs associated with data storage and processing strain budgets, demanding more cost-effective solutions. The complexity of integrating diverse systems prevents interoperability, creating data silos that prevent efficiency in day-to-day operations. Addressing these challenges is essential for the security of the public sector.
Regulatory Compliance and Governance
Navigating the regulations governing data security and privacy, which public sector entities must adhere to
Resource Allocation and Efficiency
Public sector budgets are often constrained, necessitating efficient use of resources
Data Silos and Integration
Disparate systems can create data silos, hindering effective communication and data utilization across departments and agencies
Our Approach
Detect, Monitor & Secure
HiddenLayer’s AISec Platform is purpose-built to ensure the integrity of GenAI models throughout the MLOps pipeline for the public sector. The Platform provides detection and response for GenAI and traditional AI models, safeguarding against prompt injections, adversarial AI attacks, and digital supply chain vulnerabilities.
Enhanced Security
Advanced protection for AI and ML infrastructure, mitigating the risk of data exposure and manipulation by malicious actors.
Examples include real-time security for AI models used in radio frequency, image classification, and GenAI across Defense and Civil Sector use cases.
Reduced Manpower
Minimize operating manpower and decrease the reliance on specialized cybersecurity professionals, streamlining operations and fostering a more efficient use of resources.
Interoperability
Connect between various systems and platforms, enabling AI-driven data caching and replication throughout tactical and strategic networks.
Examples include integration of HiddenLayer Model Scanner into existing CI/CD pipeline to ensure the the efficiencies of pre-trained models from public repositories.
It is important to manage the risks from the Federal Government’s own use of AI and increase its internal capacity to regulate, govern, and support responsible use of AI to deliver better results for Americans…
The Federal Government should lead the way to global societal, economic, and technological progress.”
Executive Order 14110 (Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence)
Key Capabilities
- Malware Analysis — Scans AI Models for embedded malicious code that could serve as an infection vector & launchpad for malware.
- Model Integrity — Analysis of the AI Model’s layers, components & tensors to detect tampering or corruption.
- Protects against Gen AI Prompt injection — Protect LLMs from its inputs or outputs being deliberately changed.
- Protects against Model Theft — Stop reconnaissance attempts through inference attacks, which could result in intellectual property being stolen.
- Excessive Agency — Ensure GenAI outputs do not expose backend systems, risking privilege escalation or remote code execution.
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