Anomaly Detection: K-Nearest Neighbors

In this blog, we will discuss K-nearest neighbors (KNN), a common technique in anomaly detection. We will then provide an overview of where it intersects with emerging privacy preserving technologies and how it impacts advanced analysis on multiple encrypted datasets.

Privacy-Preserving Machine Learning (PPML)

The answer to the privacy/AI conflict is privacy-preserving machine learning (PPML) – a step-by-step process to allow ML models to be trained without revealing or decrypting the data inputs.

Zero Trust Data Collaboration

Zero trust data collaboration

Why zero trust data collaboration is not only possible with PETs, but preferable for technologically forward-thinking enterprises.

What is Homomorphic Encryption?

What is Homomorphic encryption? How it works & the difference between partially, leveled & fully homomorphic encryption (FHE). 

The History of Sanctions, Part 1

The history of sanctions, and how technological advancements like PETs can enable institutions to simplify implementation of sanctions.

Inter-bank Data Sharing, the New Frontier of Fraud Detection and Prevention

If banks could share their indicators of fraud and other data drawn from their customer account and device information rather than relying solely on their own data – without revealing identifying customer and device attributes – any apprehensions of inter-bank data sharing would quickly disappear.

Building an Industry-Wide View of Risk in Financial Services

To ensure a truly comprehensive and effective approach to managing risk, it’s time to take the enterprise-wide approach one step further and transform it into industry-wide collaboration, enabling banks to investigate suspicious activity not only within their own walls, but also across them.