Network Based ZT Limitations & Emphasizing Data Centric Zero Trust Approach

The art of cyber threat landscape changes its colours whenever required and it’s not a constant static one Over the last decade, the rise of mainstream digital adoption, cloud migration, mobile computing and the continued exponential growth of unstructured data has left enterprise networks exceedingly complex to secure and, as a result, increasingly vulnerable to attacks.

Once reliable first-generation IT security solutions like firewalls, intrusion detection and endpoint security software were ill-equipped to defend against ever-evolving nature of malicious insiders, ransomware extortionists, cybercriminal hacktivists and state-sponsored attackers all of whom are now more skilled, sophisticated and well-funded.

Existing cyber defense models with an evolving threat landscape is a real and imminent need across the cyber defense community. With zero trust, legacy models like MFA, ZTNA, and other network-based approaches fail to protect unstructured data, which is often the primary asset threat actors are after. Making measurable strides toward fostering a safer cyber future will require a transformational shift to data-centric zero trust that better secures the unstructured data highly sought after by cybercriminals.

Limitations of Perimeter Protection

Perimeter protection is a key component of network based zero trust, but it doesn’t provides a full protection. An organization’s network architecture like an onion with its data assets sitting at the core. With network based zero trust principles, an organization is essentially relying on the external layers for protection without real-time visibility into the state of the core inside. Assuming malicious actors and non-malicious actors are differentiable by their characteristics and credentials. But behaviors can indicate their true intentions in reality

Once every layer is overlooked by an internal actor regardless of whether it’s a harmful attacker or harmless employee the lack of IT visibility prohibits the organization from assessing the actor’s behaviors to determine the nature of the compromise before the core data assets are infiltrated. This inability to understand the scope of the threat and mitigate its impact is a driving factor of our global cyber crisis.

Data Centric Zero Trust 

A data-centric zero-trust approach offers an alternative to legacy network-based principles. Its framework is built around the use of advanced data security solutions that generate real-time visibility to better protect data at the core; adopting an inside-out version of the “trust no one, verify everything” viewpoint at the foundation of zero trust.

Data-centric zero trust solutions can come in various forms. They leverage AI and ML to converge heightened cyber storage functionality with zero trust security principles, which enable organizations to consistently monitor the behaviors of internal actors in any environment from a data perspective. As a result, the exact moment a zero trust compromise becomes a significant threat putting their data assets at risk and then actively mount a quick and agile response to reduce damage at the core where their data assets are stored.

The rise of cyberattacks in 2021 was because of legacy and outdated practices that fail to align with the current threat landscape. By shifting to data-centric zero trust with innovative solutions that integrate enhanced levels of control to data security, organizations can boost their ability to prevent breaches, defend against attacks, and combat increasingly sophisticated cybercriminal enterprises.