User privacy and cybersecurity are two terms that often get used interchangeably when we talk about protecting our information on the internet. However, privacy and security are different areas of practice – only recently have these two areas come to intersect. In 2018, Harvard Business Review reported, “[P]rivacy and security are converging, thanks to the rise of big data and machine learning. What was once an abstract concept designed to protect expectations about our own data is now becoming more concrete, and more critical — on par with the threat of adversaries accessing our data without authorization.”Today, privacy policies and legislation often overlap with security regimes and frameworks. Privacy and security can no longer be treated as siloes, but instead should be considered as complementary to one another. Data loss prevention is one approach that can improve both user privacy and cybersecurity. In this article, we will share how DLP tools and strategies can improve both privacy and security while saving your business time, money, and resources.
What’s the difference between privacy and security?
Understanding the distinction between privacy and security is the first step toward building a system that achieves both. Privacy refers to the rights you have to control access to and the use of your personal information. Privacy encompasses the collection of data, how you allow that data to be used, who you choose to share it with, and how long data can be retained. For example, the terms and conditions you agree to when you download an app are one way you control your privacy. Security refers to how your personal information is protected. Things like encryption keys, firewalls, and VPNs all fall under the purview of cybersecurity. These are defense mechanisms that prevent unauthorized access to your data. Sometimes it helps to illustrate this difference by thinking of privacy and security in the offline world. Imagine sharing some personal information with your bank when you open a checking account. Banks usually guarantee both privacy and security. If you sign the bank’s privacy disclosure during the application process, you may have granted the bank permission to compromise some of your privacy by selling information to a marketer. Your security, however, will stay intact: no bank is going to give a marketing partner enough information to steal your identity or money. Let’s say the bank is hit by a data breach, compromising personal details stored in the bank’s database. In this scenario, both your security and your privacy could be compromised: cyber-criminals can access your money as well as your private, personal information. As we share more data online, privacy and security practices need to be coordinated and holistic. “Privacy protection and cybersecurity should be thought of as interconnected: as more and more personal information is processed or stored online, privacy protection increasingly relies on effective cybersecurity implementation by organizations to secure personal data both when it is in transit and at rest,” explains Canada’s Office of the Privacy Commissioner.
How to protect privacy and security
Ultimately, the goal of both privacy and security measures should be to keep your personally identifiable information (PII) safe. As such, organizations must implement a robust set of processes and tools that encompass user permissions and control over what data is shared, as well as protections and preventative measures to keep threats out. Data loss prevention (DLP), therefore, stands at the nexus of both privacy and security.
Develop data governance
Mastering security and complying with privacy protocols like GDPR starts with data governance. This process involves assessing what data you have, where it is stored, and what security protocols are already in place. Thoroughly understand where your customer, transaction, and proprietary data is being used and stored. Are you using platforms like Google Drive to manage your information? Are you storing data on the cloud, on external hard drives, or backed up to a third-party server? How is data transferred in and out of your business? Once you have a clear picture of how data flows through your organization, you can adopt data protection solutions like DLP to address both privacy and security requirements.
Update your technical training
The convergence of privacy and security means that these once-siloed teams now need to become multi-dimensional experts. Where privacy concerns may have previously been handled by your legal department, they are now also the domain of your IT, security and compliance teams. “From a practical perspective, this means that legal and privacy personnel will become more technical, and technical personnel will become more familiar with legal and compliance mandates,” said Harvard Business Review. “The idea of two distinct teams, operating independent of each other, will become a relic of the past.” Again, this is where a DLP tool can help. Consider compliance regimes like GDPR, CCPA, HIPAA, and PCI-DSS. The goal of these policies is to require effective management and protection of customer data to keep consumers safe. A security tool like Nightfall satisfies the needs of your compliance department by detecting and classifying PII with over 100 out-of-the-box detectors, including forms of PII specific to European countries – for example, UK Driver’s License Numbers. This tool can help a blended privacy/security team achieve its mandate with minimal manual technical set-up.
Invest in cloud DLP
The rise of remote work means more and more users are sharing information via cloud-based apps and platforms. Tools like Google Drive and Slack have seen a surge in users during the pandemic – leading to new security and privacy challenges for cloud-based tools and platforms. Luckily, cloud data loss prevention is the next generation of data security that can improve the protection of sensitive data. Cloud data loss prevention allows security teams to know where their most sensitive data is within their cloud silos and enforce access controls that trigger whenever data is accessed or shared by unauthorized users. Nightfall specifically discovers, classifies, and detects personal information (PII), protected health information (PHI), other unique identifiers, as well as credentials and secrets. Using machine learning-based detectors, Nightfall is able to automatically scan cloud environments for sensitive data with each detector having been specially trained to identify a unique token type. The platform can redact, quarantine, and delete text, strings, messages, or files containing sensitive tokens. Nightfall’s flexibility allows you to stay compliant across a variety of SaaS and IaaS environments: Slack, GitHub, Google Drive, AWS, the Atlassian suite, and more. Keep your customer and employee data safe no matter where it is. Learn more about Nightfall by scheduling a demo at the link below.