As the year progresses, 2021 will introduce further data protection challenges and vulnerability soft spots to data-driven organizations. As searing reports of breaches increase in frequency, so too do business realizations sharpen relating to the hard costs, damages, and interruptions to performance and reputations. Companies recognize they now have to find new ways to continuously secure and shield their data. More than ever, it’s essential for organizations to focus on deploying automated solutions. The major gamechanger for data-driven companies from 2021 on will be accommodating, optimizing, and protecting their remote workforces and the sensitive data they are handling.
Why Discovery at Scale Became Urgent
Breaches, theft, and data abuse have climbed steadily since the onset of COVID-19. Phishing and vishing, the latter being a phone call that uses social engineering to extract personal information, both bypass perimeter controls routinely, because an employee opening a message is not something a perimeter can prevent. Criminal groups are not the only concern either. State intelligence operations have scaled up alongside them.
The supply chain campaign of 2020 is the clearest example. A Russian team found weaknesses in supply chain technology and seeded software updates through IT backdoors, which amassed large volumes of corporate and government data for a relatively small investment. In the second stage, attackers used vulnerabilities in Microsoft code to read files and email belonging to high-value government targets, including the US Homeland Security chief, moving from one target to the next and taking data from dozens of them for months without being detected. Microsoft is the third most valuable company in the world and still took sustained reputational damage into early 2021. In April 2021 the US imposed sanctions on half a dozen Russian entities supporting that activity.
The Remote Workforce Changes the Shape of the Problem
Decentralizing offices around a growing remote workforce shifts how an organization has to think about protecting its assets. The perimeter that used to contain the work is no longer where the work happens, and the data follows the people rather than the buildings.
As breach reports become more frequent, the business understanding sharpens with them. The hard costs, the damage, and the interruption to performance and reputation stop being hypothetical, and organizations start looking for ways to secure data continuously rather than periodically. That is what makes automation the necessary answer rather than the convenient one. The volume and the distribution both exceed what manual effort can cover.
What the Shift Actually Looks Like
From the onset of the pandemic onward, large numbers of direct employees, contractors, customers, and third-party staff have worked from home, with somewhere between a third and half of them expected to stay remote permanently. Companies following the lead of Facebook, Google, Square, Twitter, and Shopify are planning to move as many people as they can.
The reasons are financial as much as cultural. Employees who relocate to lower cost of living areas can be compensated accordingly, and the largest number opting to move have come from New York City and San Francisco, which improves retention of people the business wanted to keep. Office costs fall too: REI sold its eight-acre corporate campus and Facebook scrapped earlier expansion plans. Some organizations also measure a climate benefit from removing commutes, and others find they can hire from a wider pool.
Cisco’s Q4 2020 survey of companies across American, Asia-Pacific, and European markets found 85 percent of respondents saying cybersecurity was extremely important or more important than before the pandemic. Remote working is not a temporary arrangement to be waited out.
What Automation Has to Do
For an organization to be trustworthy and to avoid costly exposure, four things need to happen without manual effort. Sensitive data has to be identified at the element level as it enters the enterprise. It has to be tagged, organized, and classified. Robust identities have to be recognized and built for very large numbers of individuals. And role-based policy has to govern how and when that data is protected, used internally, or shared.
Machine-learning powered discovery and protection has to stand up to petabytes being acquired, shared, or sold continuously, while regulatory pressure and enforcement mount and while the ethical expectations placed on companies to handle sensitive data properly become more public.
Download this free whitepaper for added insight into new trends in enterprise data discovery and protection, including:
- Why sensitive data discovery and encryption at scale is more vital than ever
- How the permanent shift to remote home offices will impact enterprise data security
- Five simple steps to secure sensitive data anywhere, anytime