Forbes: Why Your AI Is Only As Good As Your Data Integrity

Excerpt:

"Data-centric security means ensuring that even if systems are breached, data remains encrypted, verifiable and immutable. It's about integrity, not just confidentiality. If adversaries steal your data, you lose intellectual property. But if they alter your data-subtly tweaking targeting coordinates or financial ratios-they don't just steal; they destroy. A commander must trust their satellite feed implicitly, just as a CEO must trust their liquidity data.

A data-centric approach aligns security investments with enterprise value: improving insurability, aligning cyber spending with CFO-validated risk metrics and ensuring data remains unusable to attackers even after breaches.

Securing Data At Hardware, Encryption And Governance Layers

As risk shifts from systems to data, we're moving from policy-based security ("vendors promise not to train on our data") to math-based security ("vendors mathematically cannot see our data"). New technologies focus on protecting the asset, not the perimeter.

Technical Solutions

Homomorphic encryption solves the "last mile" problem. We've encrypted data at rest and in transit, but to use it-run analytics or train models-we had to decrypt it, creating vulnerability windows. Dr. Ellison Anne Williams, CEO of Enveil and former NSA researcher, calls homomorphic encryption the "holy grail" of data security. It enables computation on data while it remains encrypted, eliminating exposure windows and creating mathematically provable integrity guarantees."

Read the full article at Forbes.