Cybersecurity is undeniably a business-critical function. That’s only been reinforced over the past few months by the SolarWinds and Exchange attacks. Consequently, a recent PWC report found that 55% of enterprise executives plan to increase their cybersecurity budgets in 2021, and 51% plan to add full-time staff dedicated to cybersecurity within the year.
Meeting data privacy regulation compliance
This focus on security, however, isn’t just a reaction to more cyberattacks. It also correlates with the enormous acceleration in digital transformation initiatives over the last year. Some industry experts dubbed it the shift from “cloud speed to COVID speed.” The pandemic forced a new way of working, and this ultimately means a new way of ensuring the security of how we work. It also means that companies store and manage more data in the cloud, which comes with its own regulatory compliance challenges.
Every new process moved to the cloud, automated or made digital, has become a new vulnerability. Security teams need to manage these vulnerabilities to protect the data from a cyber-attack and ensure compliance with the latest data privacy regulations, such as the General Data Protection Regulation (GDPR) or the California Privacy Rights Act (CPRA).
Other non-compliance issues will grow over the next year, especially as companies continue to remotely onboard and offboard customers and employees. These new processes will impact how to protect data and comply with the multiple different patchwork privacy regulations from various states and countries. This is why the industry must work towards a uniform data privacy regulation, so organizations have a clear understanding of what it means to be compliant.
As challenging as 2020 was, it provided invaluable lessons that security and identity teams can apply as best practices for enterprises to adhere to regulatory and compliance standards, such as the CPRA and the GDPR. Following are three of those lessons to prioritize.
Lesson 1: Take stock of identities and lock them down
When it comes to data protection, security and compliance, organizations must keep the potential technology risk within acceptable limits, which means mobilizing efforts to identify data lakes and applications where personally identifiable information (PII) and other sensitive information is stored. Organizations should then use digital transformation as the catalyst to lock those applications down with the proper controls to prevent the unauthorized use of data and use analytics to gain visibility into the management-sensitive data.
The key to any data privacy compliance is proper data protection because under these laws, consumers retain the right to deny and revoke the collection of their data. The first step in any plan around compliance is to have a basic understanding of whose data you have, where it is, and who has access to it. This principle is the foundation of identity management and governance.
Lesson 2: Collaborate with other areas of the business to design compliance protocols
Changes to regulatory standards (both new and old) will influence risk and security efforts. Because of this, enterprises must prepare to quickly enact the necessary protocols for seamless and adequate data protection. It all starts with data discovery, which requires significant collaboration between business teams and security to map out the data captured about customers, partners, and employees. The subsequent steps include data classification, understanding how the data is processed and stored.
Overall, a sound governance framework must be put in place to ensure compliance and address organizational risk. These frameworks can only succeed if business and security teams collaborate. Unfortunately, a siloed approach to compliance will ultimately unearth more challenges – not solve them.
Lesson 3: Put identity at the core of security and compliance perimeters
As cloud use normalizes, identity management and governance become an integral part of how firms can manage privileges, access, and ensure data security and privacy. Companies should consider every workload and service in the cloud as an identity because each workload and service has access, roles, or permissions assigned to connect with other services.
Things like virtual machines, databases, containers, mobile phones, and IoT devices are all machine identities that access data on other systems while also storing and processing data that need management. Furthermore, firms should continuously monitor user access to ensure that the controls in place remain effective.
By placing identity at the center of a company’s security perimeter, an organization gains visibility into who has access to sensitive data and whether someone is accessing that data without the right permissions or need (to know) — or being exfiltrated. From there, an organization should integrate data governance protocols to identify various data repositories, adopt a zero-trust model and work towards zero-trust maturity. This process involves a shift in mindset to accept that you must approach all identities with speculation and time limits around access.
Data privacy regulation and zero-trust maturity
In addition to these three significant lessons, organizations must also recognize that zero standing privilege paves the way for zero-trust maturity – meaning that teams must determine access rights on an as-needed basis. This process forces any access to be requested, evaluated, and either accepted or denied – ensuring no identity has default access to PII or other forms of protected data.
In the end, this prevents and protects the enterprise from cyber-attacks that take advantage of standing administrative privilege and helps with regulatory compliance because it ensures that employees and administrators don’t gain excess access to private data.