Data Security at VRIFY
VRIFY Technology Inc takes the confidentiality and integrity of its customer data very seriously and we strive to assure data is protected from unauthorized access and is available when needed.
We’re proud to share that we've achieved SOC 2, Type 2 (Service Organization Control 2) compliance. This certification means we meet high standards for Security, Availability, and Confidentiality, ensuring your data is well-protected.
Our SOC 2 compliance is a testament to our commitment to building trust and credibility with you. We continuously evaluate and improve our security controls to ensure their effectiveness over time. This ongoing commitment to data security ensures that your information is always handled with the utmost care, reinforcing our strong, trust-based relationship with you.
What is SOC2 Compliance?
Created by the AICPA, SOC 2 provides criteria for handling customer data based on the various Trust Services Criteria (TSC): security, availability, and confidentiality.
Service organizations determine which of the TSC apply to their organization and then design and implement SOC 2 security controls to comply with the trust services criteria. Auditors then provide a report attesting to the fact that those criteria have been met.
Data Storage at VRIFY
We use cloud storage to provide robust security features, regular updates, and the flexibility to scale according to your needs, all while maintaining the highest level of data integrity. Your data is never stored locally, ensuring it is protected and accessible only through secure channels.
*Note that this is not a contractual agreement. Our Terms of Service is the authoritative document that outlines the data storage agreement.
Data Anonymization
When training our deep learning model using geospatial data, it is crucial to ensure data privacy and protection through anonymization. Anonymization involves transforming the data so that it cannot be traced back to individual sources while retaining its utility for model training.
At VRIFY, this process includes several steps:
Data Aggregation: Raw geospatial data is aggregated to a level where individual identifiers are removed. The data is renamed and stored using only the data types without company names and project specifications. At this point, the data is still stored on the company’s individual data silos.
Coordinate Data Masking: Specific identifying details such as spatial coordinates are transformed to an indice using a normalized data range. This way the datasets cannot be repositioned to their original coordinates and coordinate systems.
File Format Transformation: When training the image based deep learning models, the data is transformed to an image format and stored as a numerical matrix, which does not retain coordinates nor data type and specification information. The data values are then transformed and normalized to a 0 to 1 range to be ingested by the data loader.
By employing these anonymization techniques, the resulting dataset protects individual client privacy while remaining valuable for developing robust deep-learning models.
Are other companies benefiting from my data?
In Machine Learning, the performance and accuracy of an algorithm improves as more data points are used. Rest assured, your individual data remains private and inaccessible to any third parties.
However, Aggregated Data is used to train VRIFY’s Drill Targeting algorithms which allows it to continuously learn and improve, ultimately providing more accurate insights. Our Data Anonymization process ensures your geospatial data cannot be traced back to the source.
As stated in VRIFY’s Terms and Conditions, this process allows our software to continuously learn and improve, ultimately providing a better experience and more accurate insights for all users.
Protecting your privacy and ensuring data security are our top priorities, and we adhere to strict standards to safeguard your information.
Still have Questions?
Reach out to your CSM or email Support@VRIFY.com for more information.