Data security and cybersecurity are often conflated but require distinct approaches. Traditional cybersecurity, focused on access control and encryption, overlooks the complexities of data consumption. This method must be revised to address today’s risks and adapt to varied data use.
Considering the inefficiencies of 20-year-old data masking techniques and the increase in data breaches in 2023, it’s imperative to question the allocation of resources. Protecting data at its core, rather than superficial masking, could streamline security and allow for safer data consumption. The key lies in rethinking our methods to balance data accessibility and security.
Cybersecurity as we know it
Cybersecurity is the practice of safeguarding digital systems, networks, and programs from attacks that aim to steal, alter, or destroy sensitive data, extort money through ransomware, or disrupt business operations. Despite a substantial $183 billion investment in traditional security measures in 2023 and projections indicating a 14% increase in these security budgets for 2024, data breaches surged by 78%, reaching a record high. Typically, cybersecurity budgets only cover protecting applications, worrying about access rights, securing infrastructure, and hardening the network, but there is an easier and more cost-effective solution: Data security.
Data security – Key differences
Data is the most valuable commodity of a company, yet we don’t see resource allocation and time investment in data security reflecting this importance. Data security involves protecting the data itself. Once protected, the data can travel anywhere and remain protected. Having the fine granularity to safeguard the data allows you to grant users the minimum access necessary for their job functions. When someone does need to use the data, they must be authorized to do so.
With threat actors intensifying their attacks through extortion and exfiltration, now accounting for 32% of all breaches, it’s critical to reevaluate our data security strategies. We assume the bad actors will continue to steal data. However, by protecting the data itself, bad actors cannot do anything with the protected data. Effective data security neutralizes the value of data to threat actors, regardless of their access, and ensures data remains accessible to drive business growth.
Invert the security model – Protect data first
To effectively protect data, it’s crucial to invert the traditional security model and prioritize data protection. Current strategies often expose sensitive data in clear text throughout an organization, posing significant risks and inefficiencies. It is necessary to shift towards a security model that protects the data rather than just restricting access. This involves customizing protection and controls to suit different data types’ varying risks and usage needs. Implementing a zero-trust-based approach that evaluates risk and usage vectors also allows for a comprehensive spectrum of data protection, ensuring appropriate security controls are in place at every level. This modernized strategy secures the data and maintains its utility for business growth.
Zero trust data protection
Zero trust data protection techniques significantly enhance data security posture and business value. The first step to improving security and data value is identifying the most at-risk yet least accessed data. It’s essential to assess the need for clear-text visibility of high-risk data across people, processes, and systems and to consider the business impact of minimizing this risk, including factors like regulatory compliance, reputation, and insurance. If the clear form of sensitive data is unnecessary for most organizations, partners and third parties, it should differ from the default state. Protecting the data and allowing only a select few to revert it to clear text can reverse the security risk and expenditure, enabling the immediate use of de-risked data. This reversed model not only bolsters data security but also presents an opportunity to enhance the business value of data, potentially reducing costs and friction.
Becoming a data-driven organization involves more than customer acquisition and profitability. You need to balance data accessibility and security. As the McKinsey Global Institute highlights, data-driven organizations are not only 23 times more likely to acquire customers but also six times as likely to retain customers and 19 times more likely to be profitable. Yet, the challenge remains in harnessing this data while ensuring its security, as less than 2% of respondents can access sensitive data swiftly, and almost 81% of Americans express concerns over using their private data. We must evolve our data security strategies to protect our most valuable asset—data—without hindering our ability to innovate and strategize for the future.
