This chapter explores the challenges of encoding videos with homomorphic encryption, discussing the size and computational time required. It highlights the use of fully homomorphic encryption (FHE) for applications with acceptable delays and the work done to accelerate homomorphic computation using hardware. The chapter also mentions benchmark applications like machine learning scenarios and the successful experiment of retraining a model with encrypted data.