Tokenization hides data. Sometimes data must be hidden in order to satisfy compliance requirements and customers’ expectations for data privacy. A form of data protection, tokenization conceals sensitive data elements so should an organization’s data be breached, the visible tokenized data—essentially a replacement for the valuable data—means nothing.A hacker will only see characters that are meaningless.
Tokenization protects data as it travels between applications, devices, and servers, whether in the cloud or on-premises—as well as wherever it is in the world. In its most basic form, tokenization simply substitutes a randomly generated value, a “token,” for a cleartext value. A lookup table, or token vault, is kept in a secure place, to map the cleartext value to the corresponding token. A digital token is the key to reclaiming this valuable data. As soon as a user with authorization needs to access the sensitive data elements, a token affixed to that data is used to reveal it, much as a coat-check ticket enables people to retrieve valuables they store for a bit at restaurants and hotels.
There are different types of tokenization. A more sophisticated form—symbolized by Protegrity Vaultless Tokenization (PVT)—solves the time and capacity challenges found in traditional tokenization. PVT uses small, static token tables to create unique, random token values without the need fora traditional vaulted token-lookup table. Instead, PVT offers a highly scalable, flexible, and powerful protection method for structured and semi-structured data. Protection is applied at the data point, and the value of the token is based on a codebook that remains consistently responsive no matter how much data has been previously protected.
Tokenization protects the structured data that’s fed into transactional systems, such as ATMs, CRM systems, and inventory-management systems. It also safeguards the unstructured data of emails, word processing documents, PDF files, photos, and many other formats.
Facing strict data regulations from governments and heightened expectations for data privacy from individuals, organizations must effectively protect sensitive data—but they also cannot tuck it away and ignore its immense value in delivering business insights. Tokenization isn’t just effective end-to-end data protection; it lets businesses safely put aside the sensitive elements of data but still tap larger data sets to power analytics, AI-supported initiatives, containerization, and other applications that drive business.