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Published on June 4, 2021 AUTHOR PRIVACY RESEARCH TEAM
Organizations today hold a lot of consumer data. This data can range from their names and email addresses to social security numbers and banking information. Although all of this data can be seen as an asset, there is a serious liability attached to them with respect to protecting this data. Privacy regulations such as the CCPA and GDPR require organizations to protect this data at all costs or risk facing fines for non-compliance.
Before we can dive into Sensitive Data Exposure, let's first look at what sensitive data is.
Personal data is any information that relates to an identified or identifiable natural person, whereas non-personal data includes elements that do not have identifiability and uniqueness to a person. Sensitive Data, on the other hand, is any data that reveals an individuals:
Sensitive Data Exposure occurs when an organization unknowingly exposes sensitive data or when a security incident leads to the accidental or unlawful destruction, loss, alteration, or unauthorized disclosure of, or access to sensitive data. Such Data exposure may occur as a result of inadequate protection of a database, misconfigurations when bringing up new instances of datastores, inappropriate usage of data systems and more.
Sensitive Data Exposure can of the following three types:
Organizations that collect sensitive data are responsible for its protection and failure to do so can lead to heavy fines and penalties.
Lets take for example, the fines associated with Health Insurance Portability and Accountability Act (HIPAA) and Health Information Technology for Economic and Clinical Health Act (HITECH). HIPAA and HITECH protect a patient's health data and failure to do so can result in potential violations of up to $1.5 million in a year. Since these fines can continue to accumulate over the course of multiple years, this could accumulate to a large sum which can be disastrous for an organization’s growth plans.
To avoid such exorbitant amounts of fines, organizations must implement appropriate measures to protect sensitive data of their customers and prevent any breaches.
In order to protect their consumers data, organizations need to make sure they keep track of all the data stored within their systems and perform an audit. This will give them a clear picture of owners, locations, security and governance measures enabled on the data.
In order to protect data, organizations need to have a clear understanding of the data risk and allocate budgets & resources for risk mitigation activities accordingly. The more sensitive the data is, the higher the risk of harm will be. Even a small amount of highly sensitive data can have a high impact on data subjects.
Organizations must have appropriate security controls in place to avoid the occurrence of sensitive data exposures as well as to limit their impacts on data subjects.
Organizations must have an effective breach response mechanism in place to immediately respond to sensitive data exposure.
As the world becomes more digital, organizations all around the world have started to collect more and more personal data. The collection and processing of personal data help organizations to not only understand their consumers better and increase consumer satisfaction but also generate revenue. That being said, most organizations have limited visibility into personal data due to the large volume of personal data they collect and their spread across heterogeneous systems. Personal data is distributed across a large number of platforms and systems such as on-premises, hybrid, and multi-cloud data assets.
Sensitive Data Intelligence helps organizations overcome these challenges by creating visibility into personal and sensitive data across all structures of the organization. This visibility helps organizations classify datasets as per their sensitivity, assign risk scores to datasets depending on how much security a particular type of dataset needs, and link data to its correct owners (data subjects). All of this is achieved by streamlined workflows and policy-based automation.
Sensitive Data Intelligence (SDI) is a class of solutions that help organizations discover, analyze, and protect large datasets. These solutions are purpose-built and fully automated for handling petabyte-scale of data across cloud-native & non-native assets, both on-premises and multi-cloud, in structured and unstructured formats.
Securiti’s SDI solution offers the following functionalities:
Securiti can enable organizations to improve their command on the sensitive data they hold, in turn making them more compliant with global privacy regulations and a trustworthy brand amongst their customers.
To see how it works and can help your organization, request a demo today!