IDC Names Securiti a Worldwide Leader in Data Privacy
ViewOrganizations collect data from consumers every day. This data can range widely from a person's first and last name to confidential information such as bank account details. Such sensitive data needs to be protected at all times. As sensitive data continues its movement to the cloud, the ease with which it can be accessed expands.
While it enables teams to work on and off-premises from many devices, it also expands the risks of ubiquitous access and a larger surface area that malicious actors can exploit.
This article will discuss sensitive data, the types of sensitive data, and how organizations can protect their sensitive data from breaches.
Sensitive data is information that a person or organization wants to keep from being publicly available because releasing that information can lead to harm, such as identity theft or other crimes. In some cases, sensitive data is related to individuals, such as payment information, birth date, etc. In other cases, sensitive data can be proprietary corporate information.
Sensitive and special categories of personal data need extra security because the consequences of a personal data breach are more detrimental to individuals. For example, most modern smartphones store their owner’s biometric data for security. If this biometric data is compromised in a data breach, it could help criminals steal identities, create fake documents, and commit crimes.
It is critical to detect all the sensitive data in an organization's environment and identify gaps or risks in its security posture. To achieve that, organizations must develop a robust data security posture management (DSPM) strategy.
Here are some examples of sensitive data:
When measuring how sensitive or how data should be classified, think about the privacy, security, and accessibility of that information and how it might affect your organization or its clients if it were disclosed.
Privacy and security elements mandate businesses to introduce data encryption, enabling two factors to authenticate, using biometrics to confirm the identity of the user, restricting the locations where information can be found and restricting the number of times information can be used, keeping sensitive information in unconnected storage systems, etc.
Suppose an organization processes racial, ethnic, political, religious, philosophical, genetic, biometric, health, or sexual orientation data. In that case, it's no science that such data is classified as sensitive under many laws and requires a great deal of protection since it's sensitive in nature.
Unauthorized disclosure of sensitive data may result in fines, legal action, reputational damage, economic losses, and other consequences. Losing customers' trust may very well be the primary long-term effect of an authorized disclosure resulting in a data leak.
A company's most treasured asset is frequently its reputation because it takes ongoing effort to develop and protect a brand's integrity. However, even the strongest reputations can be ruined by a single scandalous incident like a data leak/unauthorized disclosure.
Furthermore, unauthorized disclosure results in obtaining access to systems where the attackers can snoop around in locations unnoticed and can do a great deal of harm and jeopardize an organization's integrity.
Under the CCPA, personal information means “any information that identifies, relates to, describes, is reasonably capable of being associated with, or could reasonably be linked, directly or indirectly, with a particular consumer or household.”
Under the CCPA, Personally Identifiable Information includes identifiers, biometric information, geolocation information, internet or other electronic network activity information, professional or employment-related information, etc. Personal Information does not include publicly available information (made public by federal or state authorities) or de-identified consumer information.
CCPA does not separately define the special categories or sensitive personal information. However, personal characteristics, behavior, religious or political convictions, sexual orientation, and financial and medical information are considered sensitive in nature. The following are four subdivisions that need to be fulfilled for information to be deemed personal under the CCPA.
This refers to information that clearly identifies a consumer or a household. Names of individuals, an image of the person, and a social security number will all be personal information under the CCPA.
This refers to information that does not identify such a person or household by virtue of its content but by virtue of its purpose. For example, it is debated that information gathered through cookies or alternate tracking methods can be classified as personal information that relates to a consumer and becomes a part of a consumer’s personal information.
Information such as drug prescriptions, dosage, drug identification number, phone number, and other information can be used to describe a consumer and falls under the category of personal information under the CCPA.
Certain tracking is embedded in the system. Although this tracking may not be intended for tracking an individual if the person is linked to the system, any information taken from the system about the individual will be classed as personal information under the CCPA.
Under the GDPR, personal data means any information relating to an identified or identifiable natural person.
Sensitive personal data is a specific set of “special categories of personal data'' that require extra security. Sensitive personal data under the GDPR include the following:
Protecting data from any breaches is never a guarantee, but there are a number of steps that can be taken to minimize the effect and sprawl of sensitive data.
Discover data and build a centralized catalog of all data assets, including all sanctioned & shadow data assets in on-premises & multicloud environments. The ability to keep track of the data is the first step toward protecting it from malicious intent and minimizing the “blast zone”.
Every data asset has various metadata associated with it that are classified into business, technical, and security. Organizations can use this metadata to determine how their PII and PHI data is protected and governed.
There are 3 types of metadata:
Once cloud-based or on-premise assets are discovered, security administrators need to know what sensitive data is stored in these assets. There are a few important categories of sensitive environment that impacts most businesses:
A sensitive data catalog provides insights into sensitive data attributes as well as security and privacy metadata such as security controls, the purpose of processing, etc.
Implement comprehensive data risk assessments that include data sensitivity, data concentration, and instances of cross-border transfers. All these parameters can be used together to assess the overall data risk score, which can be used to prioritize risk mitigation activities.
Fulfilling DSR Requests are a requirement under global privacy regulations, and failure to do so can result in heavy fines. To fulfill DSR requests in a timely manner, organizations should ensure that they can not only discover personal data but also link discovered data with users' identities automatically.
For organizations, up-to-date security, privacy, and compliance reports are required for business and legal reasons. Organizations need to build a centralized catalog of their data assets as well as discover sensitive data stored in them. Organizations can use automated discovery mechanisms to ensure their data maps and Article 30 (GDPR) reports are up to date.
Due to the exponential growth of data and potential leakage of sensitive information in the cloud, the use of Sensitive Data Intelligence solutions is needed in order to maintain visibility over data that has gone beyond the reach of on-premises tools. Securiti enables organizations to maintain complete visibility of their data stores through one portal and offers control over all data activity.
Sensitive data, in the context of data protection and privacy, refers to information that is particularly sensitive or private and requires extra protection. This includes data that, if disclosed or mishandled, could result in harm, discrimination, or privacy violations.
Examples of sensitive data include but are not limited to, personal information such as:
Sensitive data refers to information that requires special protection due to its potential to cause harm or privacy violations if mishandled. On the other hand, non-sensitive data includes information that is less likely to result in harm or privacy issues if disclosed.
The three primary types of sensitive data are:
Sensitive data refers to information that is sensitive due to its potential to cause harm or privacy issues if mishandled. Private data, on the other hand, encompasses a broader range of information that individuals may consider private, including non-sensitive personal details like email addresses or mailing addresses. While all sensitive data is private, not all private data is necessarily sensitive.
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