Layered trust boundaries are the multitiered security approach referred to as the Trust Information Security Architecture (TISA). According to the study A Layered Trust Information Security Architecture, “Current information security platforms do not deal with the different facets of information technology” and therefore struggle to protect information across complex environments. The model relies on separated interconnected systems into clearly defined trust zones so information assets are protected in a deliberate way.
This is a response to existing perimeter-based security, which assumes implicit trust once access is granted. The architecture applies security controls progressively in a way that reinforces the core concepts of confidentiality.
The first layer in the layered trust boundary establishes the foundation. Data, systems, networks, and supporting assets are identified and classified, allowing protections to be applied where they matter most. The previously mentioned layered trust study notes that “information can be considered the most important asset of any modern organization” and that securing it requires preserving “confidentiality, integrity and availability, the well-known CIA triad.” Assets are not treated as equally sensitive. The model takes into account that too many controls are expensive and often ineffective.
The second layer addresses the mechanisms that make security operational. Organizational policies translate business objectives into enforceable security expectations. The study frames this layer as turning security into a managed practice, explaining that “information security is a risk management job; the task is to manage the inherent risks of information disclosure.” Formal risk management processes guide how threats are identified and mitigated. Human factors are treated as integral, with attention to behavior, training, and accountability.
The third layer governs day-to-day operation. Documented procedures define acceptable behavior, and audits evaluate whether controls work as intended. Surrounding all of these layers is a trust layer that allows no ambiguity. The study is explicit on this point, stating that “when it comes to security, trust is zero or one. You trust your information systems, network, etc, or you do not; ‘maybe’ should be avoided.” Systems are either shown as trustworthy through evidence and verification, or they are not trusted at all. Partial trust is rejected because predictable behavior is the only reliable basis for security.
The first layer identifies and classifies data, the second puts security into action, and the third focuses on daily operations. A trust layer sits above all of these, tying them together and making it easier to see how a weakness in one area can affect the entire system. The value of TISA comes from its ability to manage different types of risk, natural, technical, and human, without overprotecting low-risk assets or wasting resources. Security efforts are matched to asset value.
A study indexed in Multidisciplinary Digital Publishing Institute (MDPI) explains, “Traditional perimeter-based network security models can no longer cope with evolving security requirements,” and zero-trust approaches emerged precisely because implicit trust inside a boundary creates blind spots that attackers can exploit.
It doesn’t conform to standards such as ISO 27001 which focuses on whether systems can actually be trusted in practice. Trust is treated as a clear decision: systems are either verified and predictable, or they are not trusted at all. This approach limits insider misuse and lateral movement that traditional perimeter-based security often fails to stop.
Email assets such as messages, attachments, mail servers, and the networks that carry them are identified and prioritized. Protections are applied using the core confidentiality, integrity, and availability principles, along with extensions like authentication and non-repudiation. The layered trust study puts it aptly, explaining, “If one does not understand what data, information, information assets, and so on, are to an organizational environment, there is no point in discussing information security, simply because one does not know what should be protected.”
This layer turns those priorities into action. Organization-specific policies define how email should be protected, including requirements for encrypted communication methods such as S/MIME or PGP. Risk management processes focus on common email threats, from phishing to malware delivery.
Human factors are treated as part of the security surface, with training aimed at reducing social engineering risk. Technical controls, including spam filtering, malware detection, and endpoint monitoring, are selected and adjusted to reflect how email-based attacks continue to evolve. The study goes on noting that “individuals’ actions and motivations have direct positive or negative influence on information security.”
It governs daily operations. Clear rules help restrict the handling of unverified attachments. Documented procedures, on the other hand, require scanning inbound and outbound traffic. Audit logs are reviewed for unusual access patterns, and continuous monitoring of email gateways helps surface vulnerabilities as they appear.
The study explains that “normatives, procedures, monitoring, and auditing will give systems administrators the tools to help them keep information, information assets, networks, systems, etc., more protected.”
The HIPAA compliant email Paubox’s use of generative AI aligns well with layer 1’s goal of targeted protection. Instead of treating all emails the same, the system analyzes context, intent, and language patterns using a combination of deep learning techniques. The approach allows phishing and malicious messages to be detected with high accuracy.
That capability matters in practice because, according to Paubox reports, while 89% of healthcare IT leaders say AI is needed for threat detection, only 44% actually use AI-powered tools, leaving a gap where advanced threats slip past legacy defenses. Paubox effectively fills that gap by adding an intelligence layer designed to catch attacks that traditional filters miss.
With regards to layer 2, rather than making rigid yes-or-no decisions, the technology accounts for uncertainty in email content and sender behavior. Messages that fall into a gray area can be flagged or temporarily quarantined instead of automatically blocked.
Layer 3 covers daily operations, monitoring, and auditing. At this level, real-time analysis of tone, writing style, and emerging attack patterns helps identify threats that bypass traditional filters. Automated response capabilities reduce risk after delivery, while monitoring tools make it easier to see how different controls interact.
Layered trust limits lateral movement by ensuring that compromise at one layer does not automatically grant access to other systems or data.
AI systems can measure uncertainty in messages or behavior and route ambiguous activity for review rather than granting or denying access blindly.
Layered trust operationalizes zero trust by enforcing continuous verification across identity, behavior, and system interactions.