Anonymized vital data for autonomous driving systems without reducing its value
Learn how Deep Natural Anonymization from brighter AI goes beyond blurring to retain data quality while complying with privacy legislation. Download the white paper to learn more.
Go beyond blurring by using a Deep Natural Anonymization solution
Autonomous driving is the future of transportation. But while many vehicles have some form of self-driving capability, completely autonomous systems need to prove their viability and safety. The key to improving these systems is to have quality data that can only be obtainable by using anonymization when developing Advanced Driving Systems (ADS). To address this challenge, Siemens has joined brighter AI to use the Deep Natural Anonymization Technique (DNAT) and make it part of the Simcenter SCAPTOR workflow.
Retain the quality of personal identification information while complying with privacy legislation
Data is a key business asset, so it's value must be always protected. Investing in protecting the long-term value of data through the use of advanced anonymization is essential to protect privacy and satisfy regulatory compliance requirements. Storing data without it will be breaching legal regulations in many countries, leading to heavy fines. If a company is found to have breached data privacy laws, consumers may question in what other areas the company is risking security.
Download this white paper to learn how using Simcenter SCAPTOR and Deep Natural Anonymization ensures data is gathered and processed most efficiently, cost-effectively, and always retains its value.