DynBlock: dynamic data encryption with Toffoli gate for IoT

The emergence of 6G networks, coupled with the expansion of smart devices, necessitates robust and efficient cryptography solutions to ensure secure communication. However, the existing resource-constrained cryptography solutions that rely on static permutation, substitution methods, variable key sizes, and fixed block size are vulnerable to quantum computing-based cryptanalysis and side-channel attacks. To address these challenges, this paper proposes a lightweight dynamic block cipher (DynBlock) algorithm. DynBlock is specifically suitable for resource-limited devices, and features a dynamic block size (64-128 bits), which is adaptable to symmetric encryption key sizes. Additionally, DynBlock includes dynamic permutation and substitution layers that enhance confusion and diffusion properties, along with a novel substitution-permutation network (SPN) algorithm that eliminates conventional substitution- and permutation-boxes. DynBlock leverages Tofoli gates and XOR operations to reduce the number of computation operations required to achieve optimal throughput and energy efficiency. Security validation of DynBlock is performed considering various metrics, including an average key avalanche effect of 53.85%, average plain-text avalanche effect of 57.82%, differential cryptanalysis (), and cryptanalysis (). Performance is compared against various state-of-the-art schemes. We evaluate DynBlock with both 3 and 5 rounds to assess its security and computational efficiency. While the 5-round configuration offers stronger resistance to cryptanalytic attacks, the 3-round setup already delivers robust security, featuring high entropy and a strong avalanche effect, making it well-suited for resource-constrained environments. It is found that DynBlock significantly improves energy efficiency and throughput compared to its predecessors. Additionally, DynBlock demonstrates resistance to quantum computing-based attacks, improved side-channel attack resilience, and enhanced randomness and entropy.