AI

5 Key Membership Inference Attack Risks Regulated Industries Cannot Ignore

5 Key Membership Inference Attack Risks Regulated Industries Cannot Ignore

A membership inference attack turns a trained AI model into an informant against the very people whose data built it. In a membership inference attack, an adversary with nothing more than query access to a model works out whether a specific individual’s record was part of the data it was trained on. It is a...

by Michal Wachstock

September 3rd, 2026 16 min read

Responsible AI for Regulated Industries: Principles, Frameworks, and How to Get It Right

Responsible AI for Regulated Industries: Principles, Frameworks, and How to Get It Right

Responsible AI is no longer optional for organizations that build AI with sensitive data. In healthcare, financial services, government, and other regulated industries, every AI system must be accurate, explainable, secure, and able to withstand regulatory scrutiny. That means proving how models were trained, protecting sensitive data throughout the AI lifecycle, reducing bias, and maintaining...

by Michal Wachstock

August 26th, 2026 14 min read

Cross-Border Data Transfers Under GDPR: What Regulated Industries Must Know

Cross-Border Data Transfers Under GDPR: What Regulated Industries Must Know

In August 2024, a single category of cross-border data transfer cost Uber 290 million euros. The Dutch Data Protection Authority found the company had moved European drivers’ personal data to servers in the United States without adequate safeguards, one of the largest transfer-related penalties in GDPR history (EDPB). A cross-border data transfer under GDPR is...

by Michal Wachstock

August 20th, 2026 10 min read

AI Data Security: Protecting AI Models and Sensitive Data

AI Data Security: Protecting AI Models and Sensitive Data

Artificial intelligence is transforming industries – from healthcare and finance to manufacturing and government – driving innovation, efficiency, and smarter decision-making. But as AI systems become more powerful, the risks they bring grow equally complex. AI doesn’t just process data; it learns from it. These systems rely on massive volumes of sensitive information, proprietary models,...

by Michal Wachstock

March 22nd, 2026 15 min read

Your Best AI Models Deserve Real Customer Data – Without the Liability Risk

Your Best AI Models Deserve Real Customer Data – Without the Liability Risk

You’re a data engineer or ML scientist. You architect models that need to generalize across unique customer environments including fraud detection, healthcare diagnostics and HR forecasting. But too often you’re held back, not by architecture, not by compute, but by the data itself. Your training sets? Synthetic or sampled proxies that fail to capture true...

by Michal Wachstock

September 17th, 2025 3 min read

LLMs Behind the Firewall and How Secure RAG Unlocks Your Hidden Data

LLMs Behind the Firewall and How Secure RAG Unlocks Your Hidden Data

Large Language Models (LLMs) are powerful when applied to public data, but their true transformative value comes from unlocking the knowledge hidden inside organizations’ own sensitive datasets. Government agencies, healthcare institutions, legal firms, and enterprises generate massive volumes of information every day, yet much of it remains siloed, underutilized, or inaccessible due to security and...

September 1st, 2025 7 min read

Why Agentic AI Demands a New Approach to Data Governance

Why Agentic AI Demands a New Approach to Data Governance

The world is currently experiencing a major shift toward more autonomous systems, known as agentic AI. These systems are capable of making independent decisions, acting on behalf of users, and even learning from their experiences. Gartner predicts that by 2028, 33% of enterprise software applications will include agentic AI, a sharp increase from less than...

by Michal Wachstock

August 19th, 2025 9 min read

Revolutionize Your Research: Meet Duality Assistant Agents

Revolutionize Your Research: Meet Duality Assistant Agents

Analysts and researchers are constantly seeking ways to unlock deeper insights from their datasets. But what if you could do this while simultaneously upholding the highest standards of data privacy and security? At Duality, we’re excited to introduce our new solution: Duality Assistant Agent, an innovative framework designed to transform how you conduct a secured...

by Adi Hirschstein

July 2nd, 2025 7 min read

Gartner AI TRiSM & Duality

Gartner AI TRiSM & Duality

What is AI TRiSM? AI TRiSM (Trust, Risk, and Security Management) is a framework introduced by Gartner to ensure the security, privacy, and governance of AI applications throughout their lifecycle. It aims to address the key risks and compliance challenges associated with deploying artificial intelligence at scale. In simple words, think of AI TRiSM like...

May 19th, 2025 8 min read

Advancing Privacy-Preserving AI: Duality’s Secure, Federated Learning with NVIDIA & Google Cloud

Advancing Privacy-Preserving AI: Duality’s Secure, Federated Learning with NVIDIA & Google Cloud

Duality v4.3 is now available! Duality’s integration of NVIDIA FLARE and Google Cloud Confidential Space combines federated learning with PETs such as TEEs to advance AI collaboration.

March 17th, 2025 7 min read

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