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What is Randtronics DPM easyData?

DPM easyData functions as a sophisticated engine for the de-identification and spoofing of data, utilizing techniques like masking, tokenization, anonymization, pseudonymization, and encryption to protect sensitive information. By employing data spoofing methods, this software can replace entire data sets or portions with non-sensitive substitutes, creating fictitious data that acts as a strong safeguard. Designed specifically for web and application server environments, it allows databases to anonymize and tokenize data while implementing masking policies for users lacking proper authorization to access sensitive materials. What sets DPM easyData apart is its ability to provide precise control, enabling administrators to delineate user permissions regarding access to specific protection measures and to specify the actions they can undertake within these guidelines. Additionally, its highly customizable framework supports a vast array of data types, delivering exceptional flexibility in defining input and token formats to address various security requirements. This versatility not only empowers organizations to uphold strict data protection standards but also facilitates the effective management of sensitive information across different scenarios. Overall, DPM easyData represents a comprehensive solution for organizations seeking to enhance their data security protocols while navigating the complexities of sensitive information management.

What is CipherTrust Tokenization?

CipherTrust Tokenization greatly reduces the costs and effort required to comply with security policies and regulations like PCI DSS, while also offering a straightforward method for protecting other sensitive information such as personally identifiable information (PII). While the market lacks universally accepted standards for tokenization, most solutions can be divided into two primary types: vaultless and vaulted tokenization, both designed to secure and anonymize sensitive data effectively. This tokenization software can be implemented across various environments, including traditional data centers, expansive big data infrastructures, or cloud services. By adopting tokenization, businesses can remove cardholder data from the PCI DSS compliance scope with minimal investment and effort, resulting in substantial savings on compliance-related costs. In the current landscape of IT infrastructures, ensuring the safe management of PII is paramount. With CipherTrust tokenization, organizations can protect PII efficiently, avoiding the typical complexities of encryption key management that often challenge software developers, thus optimizing data security workflows. This cutting-edge approach not only simplifies the compliance process but also bolsters overall data governance strategies, ultimately promoting a more secure handling of sensitive information. Moreover, it allows organizations to focus on their core business operations while maintaining high standards of data security.

Media

Media

Integrations Supported

Randtronics DPM Database Manager

Integrations Supported

.NET
Apache Cassandra
Azure Marketplace
CipherTrust Data Security Platform
Google Cloud Platform
Java
Microsoft Hyper-V
MySQL
Oracle Database
SQL Server

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Randtronics

Date Founded

2002

Company Location

Australia

Company Website

randtronics.com/products/randtronics-dpm-easydata/

Company Facts

Organization Name

Thales Cloud Security

Company Location

United States

Company Website

cpl.thalesgroup.com/encryption/tokenization

Categories and Features

Data Anonymization

Not specified

Data Masking

Not specified

Categories and Features

Data Tokenization

Not specified

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