Cloud Application Security

The AudienceRestriction element identifying the unique entity ID of the relying party is the correct answer.

In the Security Assertion Markup Language (SAML) specifications, the element (which contains ) is used to define the limitations on the use of the assertion. Specifically, the AudienceRestriction element lists the URI references (Entity IDs) of the Service Providers (SPs) for whom the assertion is intended. When an SP receives a SAML assertion, it must validate that its own unique identifier is present within the AudienceRestriction list. If the assertion was issued for the 'HR System', the AudienceRestriction would contain the HR System's Entity ID. If a user tries to replay this token against the 'Procurement System', the Procurement System should reject it because its own Entity ID is not listed in the audience, thereby preventing cross-service acceptance.

The other answers are incorrect for the following reasons:

The SubjectConfirmation methods bind the assertion to the subject (the user) or the presenter, often using mechanisms like 'Sender Vouches' or 'Holder-of-Key'. While this helps ensure the token wasn't stolen in transit, it does not explicitly scope the token to a specific destination application to prevent valid cross-service usage.

The Digital Signature ensures the integrity and authenticity of the assertion, proving it came from the trusted Identity Provider and hasn't been tampered with. However, since the Identity Provider is trusted by both the HR and Procurement systems, the signature would be valid for both; it does not restrict which specific system is allowed to consume the token.

The AttributeStatement is used to transport information about the user, such as group memberships, roles, or email addresses. It is used for authorization decisions within the application but does not define the validity scope of the token itself regarding the intended relying party.

The correct architectural strategy is to implement envelope encryption where the application service decrypts the Data Encryption Key (DEK) once and caches it in memory for a defined time-to-live (TTL) period.

In a multi-tenant SaaS environment requiring strict field-level isolation and Bring Your Own Key (BYOK), the cryptographic hierarchy typically involves a master Key Encryption Key (KEK) owned by the tenant (stored in a KMS or HSM) and a Data Encryption Key (DEK) used to encrypt the actual data fields. Calling the external Key Management Service to decrypt the DEK for every individual read operation introduces significant network latency, making sub-millisecond response times impossible. By decrypting the DEK once and caching the plaintext key in memory for a short duration, the application can perform high-speed, local AES decryption of the data fields while still respecting the tenant's control over the KEK (if the KEK is disabled, the DEK cannot be refreshed after the TTL expires).

Other options are not optimal for this scenario:

• Configuring database-level Transparent Data Encryption (TDE) generally operates at the file or page level, not the field level. Managing distinct tenant wallets for specific fields within a shared-database schema is often architecturally unsupported or introduces significant overhead at the storage layer, failing to meet the granular field-level requirement effectively.

• Processing every cryptographic operation within a dedicated Hardware Security Module (HSM) partition would introduce unacceptable latency. The network round-trip time and processing overhead for every single read operation would violate the sub-millisecond performance requirement.

• Deploying an inline tokenization proxy adds an additional hop and a lookup operation against a vault for every query. While tokenization is a valid security strategy, the question specifically asks about utilizing the cryptographic hierarchy (Encryption Keys), and the proxy approach can introduce latency bottlenecks compared to local in-memory decryption.

The correct cryptographic implementation is to integrate Format-Preserving Encryption (FPE) to generate ciphertext that mathematically preserves the identical radix and length properties of the original plaintext data.

Legacy databases with rigid schemas often lack the flexibility to increase column sizes to accommodate the data expansion associated with standard encryption modes (which typically require padding to block boundaries and Initialization Vectors). Format-Preserving Encryption (FPE) solves this specific architectural challenge by encrypting data in such a way that the output (ciphertext) has the same format (length and character set) as the input (plaintext). For example, a 16-digit credit card number is encrypted into a different 16-digit number. This allows the application to secure the data before persistence without requiring schema modifications to the underlying legacy database.

Regarding the incorrect options:

Implementing standard AES-256 in CBC mode generally results in ciphertext that is longer than the plaintext due to block padding and the necessity of storing an Initialization Vector (IV). Furthermore, encryption maximizes entropy, making the resulting ciphertext virtually uncompressible, so compression algorithms would fail to force the data into the original field size.

Utilizing a deterministic hashing algorithm is a one-way function designed for integrity verification or password storage, not for confidentiality where the original data must be retrieved. Since the application likely needs to read and use the account numbers, hashing serves the wrong purpose.

Deploying fully homomorphic encryption (FHE) allows for computation on encrypted data, but it typically results in a massive expansion of data size (ciphertext is significantly larger than plaintext) and significant performance overhead. It does not automatically resize database columns and would likely violate the strict schema constraints mentioned.