Within a Secure MLOps pipeline, the implementation of Blockchain-based Immutable Ledgers to record the hashes of all training iterations and dataset…

The statement is true. A blockchain provides an immutable and distributed ledger. By recording cryptographic hashes of datasets and model artifacts at each stage of the MLOps pipeline, a verifiable and tamper-evident audit trail is created. Any retroactive alteration to a dataset or model would change its hash. This new hash would not match the one recorded on the blockchain, making the unauthorized modification immediately detectable. This serves as a robust data integrity and provenance control, which is a core component of a secure MLOps lifecycle.

This is a True/False question, so there are no other options to evaluate.

1. Salah, K., Rehman, M. H. U., Nizamuddin, N., & Al-Fuqaha, A. (2019). Blockchain for AI: Review and open research challenges. IEEE Access, 7, 10127-10149. (Section IV.A discusses how blockchain provides data provenance, integrity, and auditability for AI/ML models and data, preventing tampering.) DOI: https://doi.org/10.1109/ACCESS.2018.2890507

2. NIST. (2018). Blockchain Technology Overview. (NISTIR 8202). (Section 2.1 explains the core properties of blockchains, including immutability, which ensures that "transactions are tamper-evident and tamper-resistant," providing a high degree of data integrity.)

3. MIT OpenCourseWare. (n.d.). 15.S12 Blockchain and Money. (Course materials explain the fundamental cryptographic principles of blockchains, including the use of hash chains to ensure that past records cannot be altered without detection, thereby guaranteeing integrity.)