Assessing the Impact of Quantum Computing on Data Encryption Practices and Information Security
Zinah Tareq Nayyef, Najwan Abed Hasan, Yasir A. F. Alaabedi, Mayasa M. Abdulrahman, Jamal Fadhil Tawfeq, Ahmed Dheyaa Radhi · Applied Data Science and Analysis · 2025
Encryption of data is a cornerstone of information security with confidentiality, integrity, and availability of sensitive information. However, the advent of quantum computing (QC) adds complexity to the classical encryption mechanisms by threatening their quantum resilience. This work looks into incorporating QC into cryptographic schemes through the evolution of an Elliptic Quantum Cryptosystem (EQC), fusing elliptic curve cryptography (ECC) and quantum annealing. The objective is to offer protection against attacks in conventional cryptographic schemes and enhance quantum attack resistance. Quantum annealing maximizes encryption through quantum fluctuations to locate best solutions, resulting in higher efficiency and reliability. The research examines top performance measures, including encryption time, decryption time, bit error rate (BER), computational efficiency, level of security, and scalability. Experimental results confirm that the proposed EQC technique has improved performance compared to existing approaches. Specifically, it takes 35 ms encryption time, 40 ms decryption time, 0.0005% BER, 80 seconds computational complexity, 9 level of security, and graded scalability as 8. These outcomes confirm the efficiency of the approach in enhancing encryption security and adaptability against quantum attacks. The problem addressed is the vulnerability of classical encryption systems to quantum advancements. By the addition of quantum-safe procedures, EQC provides a safe alternative, ensuring data confidentiality and integrity during the era of quantum. Disadvantages are the challenge in using quantum annealing and scalability problems for larger datasets. Future researches need to focus on the optimization of quantum approaches, addressing scalability issues, and studying real-world applications to ensure the generalizability of this new approach.