The rapid growth in data volumes and the increasing demand for efficient encryption place significant pressure on traditional sequential cryptographic algorithms, making it difficult for them to meet the performance requirements of modern applications, particularly in high-performance computing environments. The need for greater speed and security in these environments poses challenges, especially when traditional encryption algorithms are applied to multi-tasking and GPU-accelerated platforms. Parallel block symmetric cryptographic algorithms, leveraging multi-core processors and GPUs, offer significant improvements in both speed and security. To address these challenges, this paper presents the modification of the WBC1 algorithm, which uses a three-dimensional data representation inspired by Rubik’s cubes, to enhance its cryptographic strength and parallel processing capabilities. The proposed PWBC1 algorithm adapts the original WBC1 for parallel computing systems, including MIMD (Multiple Instruction, Multiple Data) architectures and GPU-accelerated platforms. By dividing data into independent blocks, the algorithm achieves efficient parallel encryption and decryption while maintaining high cryptographic resistance. The performance analysis demonstrates a significant reduction in execution time, making the PWBC1 algorithm suitable for large-scale data protection systems. The paper also explores the complexity, scalability, and security of the algorithm in modern computing environments, offering a promising solution for addressing contemporary cybersecurity challenges.