What is data privacy?
Data privacy, also called information privacy, is an area of data protection that addresses the proper storage, access, retention, and security of sensitive data, which helps organizations meet regulatory requirements and protect the confidentiality and immutability of their data.
What are types of sensitive data?
Data privacy is typically associated with:
- Personally identifiable information (PII) and protected health information (PHI)
- Examples: Customer names, addresses, social security numbers, credit card numbers, and health information
- Valuable or confidential data
- Examples: Financial data, operational data, intellectual property, and trade secrets
Data privacy is a subset of the broader data protection concept. Data privacy is a discipline intended to keep data safe against improper access, theft, or loss. And — especially where compliance oversight is a consideration — data privacy helps ensure proper use of personal data by giving individuals control over how their data is accessed, used, or shared.
The table below illustrates the scope, goal, and methods of data privacy:
Scope | Focuses on how personal information is collected, processed, shared, and used by organizations, with an emphasis on protecting individuals' privacy rights. |
---|---|
Goals | To ensure that individuals have control over their personal data, promoting transparency, consent, and the responsible handling of information. |
Key Methods | Implementing privacy policies, obtaining informed consent, practicing data minimization, conducting privacy impact assessments, and ensuring compliance with data regulatory standards. |
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Download NowImportance of data privacy
In the digital business landscape, establishing and maintaining robust data privacy and protection practices is not merely a regulatory requirement but a strategic imperative. There are several compelling factors that underscore the critical importance of prioritizing data privacy in the corporate landscape.
Adversaries targeting sensitive data
The pervasive threat of cyberattacks looms large over the global business ecosystem, transforming cybercrime into a highly lucrative enterprise estimated to cost the world a staggering $10.5 trillion annually by 2025. Unsurprisingly, financial motives stand as the driving force behind the vast majority of data breaches. A staggering 94.6% of data breaches are fueled by the pursuit of monetary gains, emphasizing the need for organizations to fortify their defenses against relentless adversaries seeking access to sensitive data.
Cost of data breaches
The financial toll exacted by a single data breach is a harsh reality organizations must confront. On average, businesses incur a substantial cost of $4.45 million per breach. These expenses extend beyond immediate remediation efforts, encompassing legal ramifications, regulatory fines, and the daunting task of rebuilding customer trust. The significant financial consequences of a breach underscore why proactive investment in data privacy measures is not just a precautionary measure but a fiscally responsible business strategy.
Impact on the organization
The repercussions of cybercriminals gaining access to sensitive data reverberate throughout the very fabric of an organization. Beyond the immediate financial losses, there is the potential for profound and lasting damage. The compromise of sensitive information can jeopardize intellectual property, diminish competitive edge, and tarnish an organization's reputation. The erosion of trust among clients and stakeholders is a fallout that can prove challenging to recover from, underscoring the critical need for organizations to champion data privacy as an integral aspect of their corporate responsibility.
Data privacy benefits
In a digital age where data plays a pivotal role in business success and consumer trust, prioritizing data privacy offers a myriad of advantages, including:
- Business asset management: Data is a critical asset for businesses, serving as the lifeblood that fuels various operations. Maintaining the privacy of this valuable resource enhances its integrity, reliability, and overall value to the organization.
- Brand trust: Transparency in how businesses request consent, handle personal data, and adhere to privacy practices is vital for building and maintaining trust with customers. A strong commitment to data privacy contributes to a positive brand image and fosters customer loyalty. Customers are more likely to engage with businesses they trust to handle their data responsibly, leading to improved customer satisfaction and loyalty.
- Regulatory compliance: Adhering to data privacy regulations ensures that organizations operate within the legal framework, avoiding potential fines and legal consequences. Compliance with international data privacy standards also facilitates smooth global expansion of business operations. It enables businesses to navigate diverse regulatory landscapes and engage with customers worldwide without encountering legal obstacles related to data handling and privacy.
- Lower data storage costs: Implementing data privacy measures, such as data minimization and efficient storage practices, can lead to optimized data management. This reduces unnecessary storage costs associated with holding excessive or outdated information.
- Competitive advantage: Demonstrating a strong commitment to data privacy can be a differentiator in the market. Consumers are becoming increasingly aware of the importance of their privacy, and businesses that prioritize and communicate their data protection efforts can gain a competitive edge.
Common data privacy laws and regulations
For organizations large and small, it’s important to stay up to date on the latest data privacy laws. The following are examples of laws that aim to protect users’ data privacy:
- The EU’s General Data Protection Regulation (GDPR)
- The Health Insurance Portability and Accountability Act (HIPAA)
- Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA)
- The California Online Privacy Protection Act (COPPA)
- The California Consumer Privacy Act (CCPA)
- The Utah Consumer Privacy Act (UCPA)
Ensuring data privacy compliance is imperative given the substantial repercussions of noncompliance. Organizations that fall short in adhering to data privacy laws expose themselves to hefty fines, significant individual penalties, and damage to reputation. In fact, an expensive fine is almost guaranteed if your organization violates a data privacy law. For example, a serious GDPR infringement can result in a fine of up to €20 million or 4% of the firm’s worldwide annual revenue from the preceding financial year, whichever amount is higher.
Data privacy challenges
Navigating the landscape of data privacy is crucial for organizations, but the path is not without hurdles. Despite its essential nature, the journey toward robust data privacy practices is marked by various challenges. Here's a glimpse into some of the key obstacles:
- Data sprawl: The exponential surge in enterprise data volumes propels organizations into an unyielding struggle to effectively manage their sensitive information.
- Data visibility and discovery: Locating sensitive data within an organization can be a complex endeavor. It's not uncommon for businesses to ask, "Where exactly is all of our sensitive data?"
- Data breaches: The ever-present threat of data breaches looms large. Protecting sensitive information from a data breach remains a constant concern, demanding vigilant and proactive data protection measures.
- Keeping pace with regulations: The regulatory landscape for data privacy is dynamic and diverse. Organizations find themselves in a race to keep up with the myriad regulations, each with their own set of compliance requirements.
- Insider threats: Security risks originating from within an organization pose a significant risk. Indeed, 19% of breaches. This underscores the importance of balancing trust with stringent security measures, forming a critical foundation for safeguarding against potential insider threats.
Data privacy best practices
In today’s digital business, adopting robust best practices is paramount to safeguarding sensitive information. These practices encompass a holistic approach, involving processes, governance, and cutting-edge technologies. Though the specific strategies may vary for each organization, the following best practices provide a solid foundation for building and sustaining an effective data privacy framework.
Data encryption
Data encryption is a pivotal practice involving the conversion of sensitive information into a coded format. This process ensures that even if unauthorized access occurs, the data remains confidential. Encryption serves as a critical layer in safeguarding data privacy, providing an extra barrier against potential breaches and unauthorized disclosures.
Implementing a zero trust model
Integrate the Zero Trust model into your organization's cybersecurity framework as a fundamental best practice. In a Zero Trust framework, trust is never assumed, and verification is required from anyone trying to access resources in the network, whether they are internal or external. This approach challenges the traditional notion of a secure perimeter and emphasizes continuous authentication, strict access controls, and the principle of least privilege. By incorporating the Zero Trust model, organizations not only improve their overall security posture but significantly enhance data privacy. This proactive approach minimizes the risk of unauthorized access, reducing the likelihood of data breaches and safeguarding sensitive information against evolving cyber threats.
Identity and access management
Implementing a robust identity and access management (IAM) system is paramount for ensuring the confidentiality, integrity, and availability of sensitive data. IAM serves as a foundational pillar in safeguarding data privacy by controlling and managing user access to organizational resources. Establish comprehensive user authentication processes, including multi-factor authentication (MFA), to verify identities and strengthen access controls. Regularly audit and update user permissions based on the principle of least privilege, which minimizes the risk of unauthorized access by granting individuals or systems the least amount of access necessary for their specific job duties.
Vendor management
A robust data privacy strategy for any successful organization revolves around comprehensive vendor management to ensure that external partners and third parties within the company's ecosystem strictly adhere to data protection standards and compliance regulations. To achieve this, organizations should integrate data privacy due diligence into vendor selection, emphasizing thorough assessments during the process. It is imperative to confirm that your vendors adhere to similar high standards and requirements, fostering a cohesive and secure partner network that prioritizes data privacy throughout the business ecosystem.
Training employees
It is imperative to educate employees on data privacy best practices, security protocols, and the critical importance of safeguarding sensitive information. By fostering a culture of privacy within the organization, employees become integral to the overall cybersecurity posture. It is essential to ensure that all employees undergo comprehensive cybersecurity training that covers the significance of safeguarding sensitive data and provides best practices for mitigating the risks of a data breach. Every employee is a potential line of defense against cyber threats, and this training not only strengthens the organization's security infrastructure but ensures a collective commitment to maintaining a secure and resilient work environment.
Incident response plan
A robust incident response plan is essential for organizations to effectively navigate and mitigate the impact of data breaches. This plan serves as a roadmap to prevent chaos during a security incident, outlining clear action steps, roles, and responsibilities. The primary objective is to ensure a swift and organized response, minimizing business interruptions and reducing the overall cost of recovery. By incorporating regular testing and drills, organizations can refine their incident response procedures, allowing for a comprehensive and well-coordinated approach to handling cyber incidents.
Data loss prevention
Incorporating a robust data loss prevention (DLP) strategy helps organizations safeguard sensitive information. DLP involves the implementation of specialized technologies and policies designed to monitor, detect, and block the unauthorized transmission or access of critical data. A well-designed DLP system enables real-time monitoring of data movement across networks, endpoints, and cloud storage systems, allowing for immediate intervention in the event of potential data breaches.
Customer Story:
Nij Smellinghe
Watch this case study and learn why Nij Smellinghe relies on the AI-native CrowdStrike Falcon® platform and CrowdStrike Falcon® Complete to ensure sensitive patient data stays protected.
Watch NowManage your data privacy with CrowdStrike
Adopting data privacy practices is of utmost importance for organizations, as doing so establishes a protective barrier for sensitive information. Beyond safeguarding crucial data, prioritizing data privacy nurtures customer trust and loyalty, laying the groundwork for a more resilient and trustworthy business environment. Adopting robust data privacy practices helps mitigate compliance risks and enhances an organization’s reputation as a responsible and ethical brand in today's data-driven landscape.
CrowdStrike Falcon® Data Protection has been purposefully crafted to prevent breaches and preserve the privacy and integrity of sensitive information. Falcon Data Protection — a part of the CrowdStrike Falcon® platform — provides full visibility into data in motion that is classified by both content and context for faster, more accurate egress investigations, all through a unified console. Furthermore, the Falcon platform offers comprehensive visibility and protection across the most critical areas of an organization’s data risk: your endpoints, workloads, data, and identity.