Development and testing of the effectiveness of hybrid cryptographic algorithms for protecting personal data in mobile applications

Vitalii Yasenenko

Journal: Volume 30, No. 3, 2025

Pages: 24 – 36

DOI: https://doi.org/10.62660/bcstu/3.2025.24

962 Views

Development and testing of the effectiveness of hybrid cryptographic algorithms for protecting personal data in mobile applications

Vitalii Yasenenko

Received 19.03.2025

Revised 29.07.2025

Accepted 15.09.2025

Abstract

With the rapid growth in the number of mobile applications and the volume of processed personal data, the need for effective means of the protection increased. The aim of the study was to develop hybrid cryptographic algorithms and to analyse the possibilities of the integration into mobile applications to enhance the protection of personal data. The study implemented hybrid cryptographic algorithms that combined symmetric and asymmetric encryption methods, modelled the operation using Python-based software modules, and assessed the efficiency considering the characteristics of the mobile environment. The main results showed that the combination of symmetric encryption algorithms Advanced Encryption Standard and ChaCha20 ensured complete data preservation during decryption and reduced the risk of compromise due to the two-layer encryption structure. It was also found that during testing of asymmetric methods, the Rivest-Shamir-Adleman algorithm successfully protected symmetric keys, and the Elliptic Curve Cryptography algorithm enabled both parties to compute a shared secret without transmitting the key itself, which improved resistance to interception. The results of the software implementation confirmed the identity of input and output data, demonstrating the reliability of the hybrid encryption approach. On Android platforms, Keystore, Bouncy Castle, Spongy Castle, and Conscrypt provided fast encryption using Advanced Encryption Standard (~275.6 milliseconds with hardware acceleration) and ChaCha20 (~2 milliseconds), as well as efficient key exchange via Elliptic Curve Cryptography (~15.8 milliseconds) compared to Rivest-Shamir-Adleman (~2,532.8 milliseconds), with support for post-quantum algorithms. On iPhone Operating System platforms, CryptoKit, CommonCrypto, and Open Secure Sockets Layer offered similar encryption speeds, while Secure Enclave optimised Elliptic Curve Cryptography, although post-quantum algorithms required additional optimisation. The hybrid approach reduced memory usage, making the algorithms effective for mobile devices. The obtained results could be used by mobile application developers to improve data protection in financial, medical, and corporate systems on smartphones running Android and iPhone Operating System platforms

Keywords

Advanced Encryption Standard; ChaCha20; Rivest-Shamir-Adleman; Elliptic Curve Cryptography; Android; iPhone Operating System

References

Abbas, W., Joshua, S.R., Abbas, A., & Lee, J.-H. (2025). An end-to-end GSM/SMS encrypted approach for smartphone employing advanced encryption standard (AES). ArXiv. doi: 10.48550/arXiv.2503.18859.
Ali, A.K., Raza, A., & Arif, H. (2025). AI-driven dynamic selection of post-quantum algorithms for mobile application security. Asian Bulletin of Big Data Management, 5(2), 51-62. doi: 10.62019/eq34ar93.
Alsowail, R. (2025). Advanced video encryption using the opposition lotus effect-elliptic curve cryptography in signal processing applications. Signal Image and Video Processing, 19(5), article number 409. doi: 10.1007/ s11760-025-03899-x .
Bandara, P.M., Abeyrathne, P., & Sandirigama, M. (2025). Cryptographic technologies for guaranteeing compliance of data privacy to international data protection laws – a preliminary study. In D. Dahanayake & M. Rabindrakumar (Eds.), Transformative applied research in computing, engineering, science and technology (pp. 237-243). London: CRC Press. doi: 10.1201/9781003616368-32 .
Bhimanapati, V.B., Jain, S., & Pandian, P.K. (2024). Security testing for mobile applications using AI and ML algorithms. Journal of Quantum Science and Technology, 1(2), 44-58. doi: 10.36676/jqst.v1.i2.15.
Borysenko, O., & Tymoshenko, A. (2024). Overview of personal data protection methods in the cloud environment. Infocommunication and Computer Technologies, 1(7), 31-34. doi: 10.36994/2788-5518-2024-01-07-04.
California Consumer Privacy Act. (2018, June). Retrieved from https://oag.ca.gov/privacy/ccpa .
Chen, Z., Gu, J., & Yan, H. (2023). HAE: A hybrid cryptographic algorithm for blockchain medical scenario applications. Applied Sciences, 13(22), article number 12163. doi: 10.3390/app132212163 .
Fadhil, F.A., Tawfiq, F., & Thamer, M. (2024). Enhancing data security using laplacian of gaussian and Chacha20 encryption algorithm. Journal of Intelligent Systems, 33(1), article number 20240191. doi: 10.1515/ jisys-2024-0191 .
Fan, H., Meng, L., Zheng, F., Mingyu, W., & Bowen, X. (2022). Black-box testing of cryptographic algorithms based on data characteristics. In J. Lin & Q. Tang (Eds.), Applied cryptography in computer and communications (pp. 153-169). Cham: Springer. doi: 10.1007/978-3-031-17081-2_10.
Gao, Y., Guo, L., & Zhang, T. (2023). Exploring and envisioning the application of blockchain technology for privacy data protection. Applied and Computational Engineering, 19(1), 123-131. doi: 10.54254/2755 2721/19/20231020.
General Data Protection Regulation. (2016, May). Retrieved from https://gdpr-info.eu/.
Gitonga, C. (2025). The impact of quantum computing on cryptographic systems: Urgency of quantum-resistant algorithms and practical applications in cryptography. European Journal of Information Technologies and Computer Science, 5(1), 1-10. doi: 10.24018/compute.2025.5.1.146.
Gour, A., Malhi, S.S., Singh, G., & Kaur, G. (2024). Hybrid cryptographic approach: For secure data communication using block cipher techniques. E3S Web of Conferences, 556, article number 01048. doi: 10.1051/ e3sconf/202455601048 .
Grace, A. (2025). Advancements in mobile device security: Developing AI-powered applications for enhanced protection. Retrieved from https://www.researchgate.net/publication/389173473_Advancements_in_Mobile_ Device_Security_Developing_AI-Powered_Applications_for_Enhanced_Protection .
Kalphana, K.R., Aanjankumar, S., Surya, M., Ramadevi, M.S., Ramela, K.R., Anitha, T., Nagaraj, N., & Ramaswamy, K. (2024). Prediction of android ransomware with deep learning model using hybrid cryptography. Scientific Reports, 14(1), article number 22351. doi: 10.1038/s41598-024-70544-x.
Kanagavalli, V.R., & Meenakshi, A. (2024). A survey of cryptographic data protection and machine learning. In J.A. Ruth, V.G. Mahesh, P. Visalakshi, R. Uma & A. Meenakshi (Eds.), Machine learning and cryptographic solutions for data protection and network security (pp. 1-11). London: IGI Global. doi: 10.4018/979-8-3693-4159-9.ch001 .
Khalid, R., Najat, Z., & Sayda, S.J. (2025). A hybrid approach to cloud data security using ChaCha20 and ECDH for secure encryption and key exchange. Kurdistan Journal of Applied Research, 10(1), 66-82. doi: 10.24017/ science.2025.1.5 .
Lukichov, V.V., Baryshev, Y.V., Kondratenko, N.R., & Malinovskyi, V.I. (2023). Adaptive multi-layer information protection method combining steganography and cryptography. Information technology and computer engineering, 3, 4-11. doi: 10.31649/1999-9941-2023-58-3-4-11.
Malinovskyi, V.I., Kupershtein, L.M., & Lukichov, V.V. (2024). A mathematical model for assessing cyber-threats and informational impacts in microcontrollers. Information technology and computer engineering, 59(1), 69-82. doi: 10.31649/1999-9941-2024-59-1-69-82 .
Muthaura, A., & Kandiri, J. (2024). Data protection in healthcare information systems using cryptographic algorithm with Base64 512 bits. Open Journal for Information Technology, 7(1), 11-22. doi: 10.32591/coas. ojit.0701.02011m .
Neve, R., & Bansode, R. (2024). Attack analysis on hybrid-SIMON-SPECKey lightweight cryptographic algorithm for IoT applications. Indian Journal of Science and Technology, 17(10), 932-940. doi: 10.17485/IJST/v17i10.2811 .
Nugroho, W.B., Susanto, A., Sari, A., Rachmawanto, E.H., & Doheir, M. (2024). A robust and imperceptible for digital image encryption using Chacha20. Jurnal Teknik Informatika, 5(2), 397-404. doi: 10.52436/1.jutif.2024.5.2.1470 .
Nwatuzie, G.A., Ijiga, O.M., Idoko, I.P., Enyejo, L.A., & Ali, E.O. (2025). Design and evaluation of a user-centric cryptographic model leveraging hybrid algorithms for secure cloud storage and data integrity. American Journal of Innovation in Science and Engineering, 4(2), 49-65. doi: 10.54536/ajise.v4i2.4482.
Ogwara, F., Petrova, K., Yang, M.L., & MacDonell, S.G. (2025). Mindpres: A hybrid prototype system for comprehensive data protection in the user layer of the mobile cloud. Sensors, 25(3), article number 670. doi: 10.3390/s25030670 .
Pitale, R.R., Tajane, K.D., Mahajan, P.B., Nehate, N.S., Mulimani, A.J., & Lokhande, D.S. (2024). Cryptographic algorithm development and application for encryption and decryption. In D. Goyal, A. Kumar, D. Singh, M. Paprzycki, P. Jain, B.B. Gupta & U.P. Singh (Eds.), ICIMMI ‘23: Proceedings of the 5th international conference on information management & machine intelligence (article number 27). New York: Association for Computing Machinery. doi: 10.1145/3647444.3647853 .
Prodduturi, S.M. (2025). Cryptography in iOS: A study of secure data storage and communication techniques. International Journal on Science and Technology, 16(1). doi: 10.71097/IJSAT.v16.i1.1403 .
Sayed, M.A. (2024). A comparative study of machine learning-based and traditional cryptographic methods for personal data encryption. ResearchGate. doi: 10.13140/RG.2.2.33661.88803 .
Semerenska, V. (2025). Quantum-resistant cryptographic algorithms for critical infrastructures. Visnyk of Kherson National Technical University, 2(1), 204-209. doi: 10.35546/kntu2078-4481.2025.1.2.27.
Sereda, A., Datsenko, I., Pavlenko, V., & Samarai, V. (2023). Stability and efficiency of cryptographic algorithms used in mobile devices. Infocommunication and Computer Technologies, 2(4), 178-190. doi: 10.36994/2788 5518-2022-02-04-21 .
Vimala, J.C. (2023). Securing cloud environments: A comparative analysis of RSA and MRGA for enhanced data protection. Journal on Cloud Computing, 10(1), 38-46. doi: 10.26634/jcc.10.1.19937.
Vinothkumar, M., & Ram, S. (2025). Blockchain-based modified AES with chaotic random key generation for secured E-medical data sharing. CLEI Electronic Journal, 28(2). doi: 10.19153/cleiej.28.2.14.
Yan, Y. (2022). The overview of elliptic curve cryptography (ECC). Journal of Physics Conference Series, 2386, article number 012019. doi: 10.1088/1742-6596/2386/1/012019 .
Yasqi, Z., Hayaty, N., & Bettiza, M. (2025). Cryptography of Chacha20 and RSA algorithms for text security. Journal of Computer Networks Architecture and High Performance Computing, 7(1), 290-301. doi: 10.47709/ cnahpc.v7i1.5345 .

Suggested citation

Yasenenko, V. (2025). Development and testing of the effectiveness of hybrid cryptographic algorithms for protecting personal data in mobile applications. Bulletin of Cherkasy State Technological University, 30(3), 24-36. https://doi.org/10.62660/bcstu/3.2025.24

[1] Abbas, W., Joshua, S.R., Abbas, A., & Lee, J.-H. (2025). An end-to-end GSM/SMS encrypted approach for smartphone employing advanced encryption standard (AES). ArXiv. doi: 10.48550/arXiv.2503.18859.

[2] Ali, A.K., Raza, A., & Arif, H. (2025). AI-driven dynamic selection of post-quantum algorithms for mobile application security. Asian Bulletin of Big Data Management, 5(2), 51-62. doi: 10.62019/eq34ar93.

[3] Alsowail, R. (2025). Advanced video encryption using the opposition lotus effect-elliptic curve cryptography in signal processing applications. Signal Image and Video Processing, 19(5), article number 409. doi: 10.1007/ s11760-025-03899-x .

[4] Bandara, P.M., Abeyrathne, P., & Sandirigama, M. (2025). Cryptographic technologies for guaranteeing compliance of data privacy to international data protection laws – a preliminary study. In D. Dahanayake & M. Rabindrakumar (Eds.), Transformative applied research in computing, engineering, science and technology (pp. 237-243). London: CRC Press. doi: 10.1201/9781003616368-32 .

[5] Bhimanapati, V.B., Jain, S., & Pandian, P.K. (2024). Security testing for mobile applications using AI and ML algorithms. Journal of Quantum Science and Technology, 1(2), 44-58. doi: 10.36676/jqst.v1.i2.15.

[6] Borysenko, O., & Tymoshenko, A. (2024). Overview of personal data protection methods in the cloud environment. Infocommunication and Computer Technologies, 1(7), 31-34. doi: 10.36994/2788-5518-2024-01-07-04.

[7] California Consumer Privacy Act. (2018, June). Retrieved from https://oag.ca.gov/privacy/ccpa .

[8] Chen, Z., Gu, J., & Yan, H. (2023). HAE: A hybrid cryptographic algorithm for blockchain medical scenario applications. Applied Sciences, 13(22), article number 12163. doi: 10.3390/app132212163 .

[9] Fadhil, F.A., Tawfiq, F., & Thamer, M. (2024). Enhancing data security using laplacian of gaussian and Chacha20 encryption algorithm. Journal of Intelligent Systems, 33(1), article number 20240191. doi: 10.1515/ jisys-2024-0191 .

[10] Fan, H., Meng, L., Zheng, F., Mingyu, W., & Bowen, X. (2022). Black-box testing of cryptographic algorithms based on data characteristics. In J. Lin & Q. Tang (Eds.), Applied cryptography in computer and communications (pp. 153-169). Cham: Springer. doi: 10.1007/978-3-031-17081-2_10.

[11] Gao, Y., Guo, L., & Zhang, T. (2023). Exploring and envisioning the application of blockchain technology for privacy data protection. Applied and Computational Engineering, 19(1), 123-131. doi: 10.54254/2755 2721/19/20231020.

[12] General Data Protection Regulation. (2016, May). Retrieved from https://gdpr-info.eu/.

[13] Gitonga, C. (2025). The impact of quantum computing on cryptographic systems: Urgency of quantum-resistant algorithms and practical applications in cryptography. European Journal of Information Technologies and Computer Science, 5(1), 1-10. doi: 10.24018/compute.2025.5.1.146.

[14] Gour, A., Malhi, S.S., Singh, G., & Kaur, G. (2024). Hybrid cryptographic approach: For secure data communication using block cipher techniques. E3S Web of Conferences, 556, article number 01048. doi: 10.1051/ e3sconf/202455601048 .

[15] Grace, A. (2025). Advancements in mobile device security: Developing AI-powered applications for enhanced protection. Retrieved from https://www.researchgate.net/publication/389173473_Advancements_in_Mobile_ Device_Security_Developing_AI-Powered_Applications_for_Enhanced_Protection .

[16] Kalphana, K.R., Aanjankumar, S., Surya, M., Ramadevi, M.S., Ramela, K.R., Anitha, T., Nagaraj, N., & Ramaswamy, K. (2024). Prediction of android ransomware with deep learning model using hybrid cryptography. Scientific Reports, 14(1), article number 22351. doi: 10.1038/s41598-024-70544-x.

[17] Kanagavalli, V.R., & Meenakshi, A. (2024). A survey of cryptographic data protection and machine learning. In J.A. Ruth, V.G. Mahesh, P. Visalakshi, R. Uma & A. Meenakshi (Eds.), Machine learning and cryptographic solutions for data protection and network security (pp. 1-11). London: IGI Global. doi: 10.4018/979-8-3693-4159-9.ch001 .

[18] Khalid, R., Najat, Z., & Sayda, S.J. (2025). A hybrid approach to cloud data security using ChaCha20 and ECDH for secure encryption and key exchange. Kurdistan Journal of Applied Research, 10(1), 66-82. doi: 10.24017/ science.2025.1.5 .

[19] Lukichov, V.V., Baryshev, Y.V., Kondratenko, N.R., & Malinovskyi, V.I. (2023). Adaptive multi-layer information protection method combining steganography and cryptography. Information technology and computer engineering, 3, 4-11. doi: 10.31649/1999-9941-2023-58-3-4-11.

[20] Malinovskyi, V.I., Kupershtein, L.M., & Lukichov, V.V. (2024). A mathematical model for assessing cyber-threats and informational impacts in microcontrollers. Information technology and computer engineering, 59(1), 69-82. doi: 10.31649/1999-9941-2024-59-1-69-82 .

[21] Muthaura, A., & Kandiri, J. (2024). Data protection in healthcare information systems using cryptographic algorithm with Base64 512 bits. Open Journal for Information Technology, 7(1), 11-22. doi: 10.32591/coas. ojit.0701.02011m .

[22] Neve, R., & Bansode, R. (2024). Attack analysis on hybrid-SIMON-SPECKey lightweight cryptographic algorithm for IoT applications. Indian Journal of Science and Technology, 17(10), 932-940. doi: 10.17485/IJST/v17i10.2811 .

[23] Nugroho, W.B., Susanto, A., Sari, A., Rachmawanto, E.H., & Doheir, M. (2024). A robust and imperceptible for digital image encryption using Chacha20. Jurnal Teknik Informatika, 5(2), 397-404. doi: 10.52436/1.jutif.2024.5.2.1470 .

[24] Nwatuzie, G.A., Ijiga, O.M., Idoko, I.P., Enyejo, L.A., & Ali, E.O. (2025). Design and evaluation of a user-centric cryptographic model leveraging hybrid algorithms for secure cloud storage and data integrity. American Journal of Innovation in Science and Engineering, 4(2), 49-65. doi: 10.54536/ajise.v4i2.4482.

[25] Ogwara, F., Petrova, K., Yang, M.L., & MacDonell, S.G. (2025). Mindpres: A hybrid prototype system for comprehensive data protection in the user layer of the mobile cloud. Sensors, 25(3), article number 670. doi: 10.3390/s25030670 .

[26] Pitale, R.R., Tajane, K.D., Mahajan, P.B., Nehate, N.S., Mulimani, A.J., & Lokhande, D.S. (2024). Cryptographic algorithm development and application for encryption and decryption. In D. Goyal, A. Kumar, D. Singh, M. Paprzycki, P. Jain, B.B. Gupta & U.P. Singh (Eds.), ICIMMI ‘23: Proceedings of the 5th international conference on information management & machine intelligence (article number 27). New York: Association for Computing Machinery. doi: 10.1145/3647444.3647853 .

[27] Prodduturi, S.M. (2025). Cryptography in iOS: A study of secure data storage and communication techniques. International Journal on Science and Technology, 16(1). doi: 10.71097/IJSAT.v16.i1.1403 .

[28] Sayed, M.A. (2024). A comparative study of machine learning-based and traditional cryptographic methods for personal data encryption. ResearchGate. doi: 10.13140/RG.2.2.33661.88803 .

[29] Semerenska, V. (2025). Quantum-resistant cryptographic algorithms for critical infrastructures. Visnyk of Kherson National Technical University, 2(1), 204-209. doi: 10.35546/kntu2078-4481.2025.1.2.27.

[30] Sereda, A., Datsenko, I., Pavlenko, V., & Samarai, V. (2023). Stability and efficiency of cryptographic algorithms used in mobile devices. Infocommunication and Computer Technologies, 2(4), 178-190. doi: 10.36994/2788 5518-2022-02-04-21 .

[31] Vimala, J.C. (2023). Securing cloud environments: A comparative analysis of RSA and MRGA for enhanced data protection. Journal on Cloud Computing, 10(1), 38-46. doi: 10.26634/jcc.10.1.19937.

[32] Vinothkumar, M., & Ram, S. (2025). Blockchain-based modified AES with chaotic random key generation for secured E-medical data sharing. CLEI Electronic Journal, 28(2). doi: 10.19153/cleiej.28.2.14.

[33] Yan, Y. (2022). The overview of elliptic curve cryptography (ECC). Journal of Physics Conference Series, 2386, article number 012019. doi: 10.1088/1742-6596/2386/1/012019 .

[34] Yasqi, Z., Hayaty, N., & Bettiza, M. (2025). Cryptography of Chacha20 and RSA algorithms for text security. Journal of Computer Networks Architecture and High Performance Computing, 7(1), 290-301. doi: 10.47709/ cnahpc.v7i1.5345 .