Cryptographic Algorithm Performance Assessment for AI Systems: ARIA, ZUC, AES, Camellia, and HC-256

Authors

DOI:

https://doi.org/10.51173/ijds.v3i2.74

Keywords:

ARIA, ZUC, AES, Camellia, HC256

Abstract

With the expansion of AI applications into new horizons, security issues have become a top priority. Traditional AI systems are not very secure and are vulnerable to attacks and data breaches. The interconnected world we live in requires data to be kept private, protected, and verified, which can be achieved through modern security measures that incorporate cryptographic algorithms. This study evaluates the efficacy of five cryptographic algorithms, ARIA, ZUC, Advanced Encryption Standard (AES), Camellia, and HC256, regarding key generation duration, encryption and decryption speeds, and memory consumption to identify the optimal solution for practical implementations. Results show HC256 achieving the fastest encryption and decryption times of 105.6 ms and 75.6 ms, respectively, and the lowest memory usage of 1.28 MB for encryption and 1.38 MB for decryption, proving it is the most efficient in performance-sensitive settings. AES demonstrated balanced performance with moderate encryption and decryption times (116.6 ms and 115.6 ms, respectively) and relatively low memory consumption (6.36 MB), while maintaining strong cryptographic robustness. Camellia demonstrated strong cryptographic robustness according to previous literature; however, it exhibited the lowest computational efficiency in the present experimental evaluation, with the highest encryption and decryption times among the tested algorithms, but was found to yield the lowest efficiency for real-time applications, with the greatest encryption and decryption times of 1886.8 ms and 687 ms, respectively. ARIA and ZUC also exhibit different trade-offs, with ZUC showing moderate efficiency and ARIA requiring greater resources.

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References

H. Taherdoost, T.-V. Le, and K. Slimani, "Cryptographic Techniques in Artificial Intelligence Security: A Bibliometric Review," Cryptography, vol. 9, no. 1, p. 17, Mar. 2025, doi: 10.3390/cryptography9010017.

I. K. Ogundoyin, "Comparative Analysis and Performance Evaluation of Cryptographic Algorithms," UNIOSUN Journal of Engineering and Environmental Sciences, vol. 4, no. 1, Mar. 2022, doi: 10.36108/ujees/2202.40.0140.

M. P. R, P. Dharshini, and S. P. K, "EnConvo: Secure End-to-End Encrypted Messaging Application," in 2025 International Conference on Electronics and Renewable Systems (ICEARS), IEEE, Feb. 2025, pp. 995–1002. doi: 10.1109/ICEARS64219.2025.10940216.

B. E. H. H. Hamouda, "Comparative Study of Different Cryptographic Algorithms," Journal of Information Security, vol. 11, no. 03, pp. 138–148, 2020, doi: 10.4236/jis.2020.113009.

I. Afrianto, A. Heryandi, and A. Finandhita, "E-document autentification with digital signature model for smart city in Indonesia," Journal of Engineering Science and Technology, vol. 14, 2020.

H. S. Abdulla and A. M. Aladdin, "Enhancing Design and Authentication Performance Model: A Multilevel Secure Database Management System," Future Internet, vol. 17, no. 2, p. 74, Feb. 2025, doi: 10.3390/fi17020074.

R. K. Muhammed, Z. N. Rashid, and S. J. Saydah, "A Hybrid Approach to Cloud Data Security Using ChaCha20 and ECDH for Secure Encryption and Key Exchange," Kurdistan Journal of Applied Research, vol. 10, no. 1, pp. 66–82, Mar. 2025, doi: 10.24017/science.2025.1.5.

R. K. Muhammed, K. H. Ali Faraj, J. F. G. Mohammed, T. N. Ahmad Al Attar, S. J. Saydah, and D. A. Rashid, "Automated Performance analysis E-services by AES-Based Hybrid Cryptosystems with RSA, ElGamal, and ECC," Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 3, pp. 84–91, Jul. 2024, doi: 10.25046/aj090308.

S. Fatima, T. Rehman, M. Fatima, S. Khan, and M. A. Ali, "Comparative Analysis of AES and RSA Algorithms for Data Security in Cloud Computing," in The 7th International Electrical Engineering Conference, Basel Switzerland: MDPI, Jul. 2022, p. 14. doi: 10.3390/engproc2022020014.

S. D. Jonathan, J. S. Paul, N. C. Gowda, B. J. Ambika, and K. K. PN, "Comparative Analysis of Cryptographic Algorithms," International Journal of Human Computations & Intelligence, vol. 2, no. 5, pp. 212–219, 2023.

R. K. Muhammed et al., "Comparative Analysis of AES, Blowfish, Twofish, Salsa20, and ChaCha20 for Image Encryption," Kurdistan Journal of Applied Research, vol. 9, no. 1, pp. 52–65, May 2024, doi: 10.24017/science.2024.1.5.

M. Khadji, S. Khoulji, and M. L. Kerkeb, "EFFICIENT BIG DATA SECURITY: EVALUATING THE PERFORMANCE OF A PROPOSED HYBRID KEY MANAGEMENT ALGORITHM USING LIGHTWEIGHT CRYPTOGRAPHY," J. Theor. Appl. Inf. Technol., vol. 101, no. 13, 2023.

X. Song, M. Shi, Y. Zhou, and E. Wang, "An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher," Entropy, vol. 24, no. 5, p. 742, May 2022, doi: 10.3390/e24050742.

D. Lee and S. Hong, "Improved Quantum Rebound Attacks on Double Block Length Hashing with Round-Reduced AES-256 and ARIA-256," IACR Transactions on Symmetric Cryptology, vol. 2024, no. 3, pp. 238–265, Sep. 2024, doi: 10.46586/tosc.v2024.i3.238-265.

K. P. Premalatha, K. K. Sahu, and M. M. Gour, "Examining the Efficiency of Implemented Cryptographic Algorithms for Blockchain Technologies," in 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), IEEE, Jun. 2024, pp. 1–6. doi: 10.1109/ICCCNT61001.2024.10725567.

F. Liu, W. Meier, S. Sarkar, G. Wang, R. Ito, and T. Isobe, "New Cryptanalysis of ZUC-256 Initialization Using Modular Differences," IACR Transactions on Symmetric Cryptology, pp. 152–190, Sep. 2022, doi: 10.46586/tosc.v2022.i3.152-190.

S. J. Saydahd, R. K. Muhammed, S. A. Hassan, and A. M. Aladdin, "A Comparative Performance Evaluation of Hybrid Encryption Techniques Using ECC, RSA, AES, and ChaCha20 for Secure Data Transmission," Iraqi Journal of Industrial Research, vol. 12, no. 2, pp. 157–172, Dec. 2025, doi: 10.53523/ijoirVol12I2ID598.

S. SR, U. N, C. R, and A. CM, "Comparison Between Encryption Algorithms: A Performance and Security Perspective," International Journal on Science and Technology, vol. 16, no. 3, Sep. 2025, doi: 10.71097/IJSAT.v16.i3.7986.

Y. Oh, K. Jang, Y. Yang, and H. Seo, "Quantum Implementation and Analysis of ARIA," in 2024 Silicon Valley Cybersecurity Conference (SVCC), IEEE, Jun. 2024, pp. 1–7. doi: 10.1109/SVCC61185.2024.10637311.

S. Wang, R. Zhao, Z. Yu, and L. Wang, "Optimized implementations of stream cipher ZUC-256 algorithm," in 2022 4th International Academic Exchange Conference on Science and Technology Innovation (IAECST), IEEE, Dec. 2022, pp. 952–956. doi: 10.1109/IAECST57965.2022.10061968.

L. Liu and X. Liu, "Research on the New Camellia Variety' Four Seasons Treasure' and Its Applications," International Journal of Agriculture and Food Sciences Research, vol. 3, no. 3, pp. 18–22, Oct. 2025, doi: 10.62051/ijafsr.v3n3.04.

D. O. Hasan and A. M. Aladdin, "Sleep-Related Consequences of the COVID-19 Pandemic: A Survey Study on Insomnia and Sleep Apnea Among Affected Individuals," Insights in Public Health Journal, vol. 5, no. 2, Jan. 2025, doi: 10.20884/1.iphj.2024.5.2.12972.

D. O. Hasan et al., "Perspectives on the Impact of E-Learning Pre- and Post-COVID-19 Pandemic—The Case of the Kurdistan Region of Iraq," Sustainability, vol. 15, no. 5, p. 4400, Mar. 2023, doi: 10.3390/su15054400.

T.-H. Yoo, J. Kivilinna, and C.-H. Cho, "AVX-Based Acceleration of ARIA Block Cipher Algorithm," IEEE Access, vol. 11, pp. 77403–77415, 2023, doi: 10.1109/ACCESS.2023.3298026.

S. Eum, H. Kim, H. Kwon, M. Sim, G. Song, and H. Seo, "Parallel Implementations of ARIA on ARM Processors and Graphics Processing Unit," Applied Sciences, vol. 12, no. 23, p. 12246, Nov. 2022, doi: 10.3390/app122312246.

Y. Y. ZHU et al., "COMPARATIVE TRANSCRIPTOMICS ANALYSIS OF HIGH AND LOW YIELD CAMELLIA OLEIFERA (OIL-CAMELLIA) CLONES," Appl. Ecol. Environ. Res., vol. 23, no. 1, pp. 475–487, 2025, doi: 10.15666/aeer/2301_475487.

E. J. Madarro-Capó, E. C. Ramos Piñón, G. Sosa-Gómez, and O. Rojas, "Practical Improvement in the Implementation of Two Avalanche Tests to Measure Statistical Independence in Stream Ciphers," Computation, vol. 12, no. 3, p. 60, Mar. 2024, doi: 10.3390/computation12030060.

M. S. Abdulkarim, A. Ibrahim Mustafa, S. R. Mohammed-Taha, A. M. Aladdin, D. O. Hasan, and T. A. Rashid, "Multi-objective Optimization Vectors," in Multi-objective Optimization Techniques, Boca Raton: CRC Press, 2025, pp. 242–272. doi: 10.1201/9781003601555-13.

A. I. Mustafa, A. M. Aladdin, S. R. Mohammed-Taha, D. O. Hasan, and T. A. Rashid, "Is PSO the Ultimate Algorithm or Just Hype?," Jan. 05, 2025. doi: 10.36227/techrxiv.173609965.50383071/v1.

A. M. Aladdin et al., "Fitness-Dependent Optimizer for IoT Healthcare Using Adapted Parameters," in Practical Artificial Intelligence for Internet of Medical Things, Boca Raton: CRC Press, 2023, pp. 45–61. doi: 10.1201/9781003315476-3.

A. M. Aladdin and T. A. Rashid, "LEO: Lagrange elementary optimization," Neural Comput. Appl., May 2025, doi: 10.1007/s00521-025-11225-2.

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Published

2026-05-30

How to Cite

Muhammed, R. K., Aladdin, A. M., Hassan , S. A., Abdulla, H. S., Ahmed , M. A., & Sayda , S. J. (2026). Cryptographic Algorithm Performance Assessment for AI Systems: ARIA, ZUC, AES, Camellia, and HC-256. InfoTech Spectrum: Iraqi Journal of Data Science , 3(2), 25–43. https://doi.org/10.51173/ijds.v3i2.74

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