The adoption of cloud storage and processing has exponentially increased in recent years, but concerns about data privacy and security have also risen in parallel. These terms are often used interchangeably, but they are not the same thing. In this post, we'll explore why this isn't the case and show how you can have both data security and privacy in the cloud.
Data security refers to the measures taken to protect assets and environments that hold data from unauthorized access, alteration, destruction, or disruption. In contrast, data privacy is about the right of individuals to control how their personal information is collected, used, shared and ensuring that it is protected.
It is important to note that data security and data privacy are not mutually exclusive. Both are achievable and interdependent. A secure system that protects personal information from unauthorized access is essential for ensuring data privacy. Similarly, the implementation of privacy policies and regulations can help ensure the secure handling of personal information.
One key consideration in achieving data privacy and data security is protecting the right data sets, finding the sensitive data. Understanding how sensitive data is being used, why it's being used, and where it resides can help to ensure its security and related compliance. By practicing data classification and data inventory, businesses can ensure that they're protecting the right data from malicious threats, addressing responsible governance, and enforcing data security.
Data classification is a critical component in developing effective data security and privacy policies, as part of a broader data security strategy. By classifying data based on its sensitivity level, policies can be tailored to protect data based on its level of risk.
Furthermore, data classification is an essential tool to create visibility into where the organization has sensitive data, allowing it to adhere to compliance requirements where end-users have asks regarding their personal information.
Organizational policies can be designed to meet both by including measures that prevent unauthorized access to data while also ensuring compliance with privacy regulations. An organization can implement access controls and encryption to protect sensitive data from unauthorized access while establishing policies and procedures for obtaining user consent and managing data processing in compliance with privacy regulations.
Without a clear understanding of ‘who’ has access to sensitive data and ‘how’ that data is being used, it's difficult to maintain control and ensure that the data is not being accessed or shared inappropriately.
Specifically, knowing who or what has permissions to access every sensitive data store, and being able to track when access occurs, is essential for maintaining privacy and preventing data breaches. By implementing appropriate access controls and monitoring tools, businesses can limit access to sensitive data and detect any anomalies.
Understanding how data is being used within the business and with third parties is also important for compliance with privacy regulations. Businesses are required to follow specific guidelines for the collection, use, and sharing of sensitive data, and failing to comply with these regulations can result in legal and financial penalties.
Data security is essential for businesses of all sizes, but identifying and preventing security breaches can be a daunting task. Fortunately, data security tools can help businesses identify potential security and compliance gaps, measure data risk, and enforce policies to protect data from external and internal threats.
One such tool is a policy engine, like the one found in DSPM. A policy engine can help businesses improve their data security and privacy by analyzing access controls and usage patterns to identify abnormalities, alerting the business to potential security breaches or privacy violations.
By identifying areas of noncompliance with regulations and best practices, the policy engine can help businesses take proactive steps to improve their data security and privacy, such as suggesting changes to access controls or data usage policies to reduce the risk of data breaches or privacy violations. Additionally, the policy engine can provide recommendations for improving data security and privacy, ultimately helping businesses to stay compliant with regulations, reduce the risk of data breaches and privacy violations, and protect their reputation and customer trust.
When a policy engine identifies a potential violation or risk, it can provide step-by-step instructions for remediation and integrate with existing automation or workflow management systems, like JIRA, Zendesk, or Slack, to manage the end-to-end process.
These integrations can help businesses quickly address potential data breaches or privacy violations, reducing the risk of data exposure or loss. By providing clear instructions for remediation and then integrating with an organization's existing systems, businesses can streamline the process and ensure timely and effective issue resolution.
This also helps businesses stay compliant with privacy regulations by maintaining a record of remediation efforts and ensuring that necessary steps are taken to address potential violations.
Both data security and data privacy are achievable and interdependent. By implementing the right strategies and tools, businesses can have both security and privacy of their data. Protecting the right data sets, understanding data usage and access, and using data security and data privacy tools are all important components of any organization's overall data protection strategy.