A New Hybrid Technique for Data Encryption in Distributed Computing Systems

Abstract

Distributed computing environments such as cloud computing, Internet of Things (IoT), edge computing, and distributed databases require secure and efficient data protection mechanisms. Traditional encryption methods often face challenges related to scalability, computational overhead, and secure key management. This paper proposes a hybrid encryption technique that combines Advanced Encryption Standard (AES) for fast data encryption, RSA/ECC for secure key exchange, and SHA-256 for data integrity and authentication. The proposed framework enhances confidentiality, integrity, and resistance against cyber threats including brute-force, replay, and man-in-the-middle attacks. Performance evaluation based on encryption time, decryption time, throughput, memory utilization, and security strength demonstrates improved efficiency and stronger security compared to conventional single-algorithm approaches. The proposed model provides a scalable, lightweight, and secure solution for next-generation distributed computing systems

Introduction

The rapid growth of distributed computing systems, including cloud computing, big data platforms, and the Internet of Things (IoT), has transformed data storage, processing, and communication by enabling scalable and efficient distributed operations. However, their decentralized architecture introduces significant security challenges, such as protecting data confidentiality, integrity, and secure communication between nodes. Since sensitive information is often transmitted over public networks and stored across multiple locations, it is vulnerable to cyber threats including unauthorized access, data breaches, and malicious attacks. Encryption is therefore a fundamental security mechanism that safeguards data by converting plaintext into unreadable ciphertext accessible only to authorized users.

The literature emphasizes that encryption is essential across IoT, cloud computing, and distributed environments. Traditional cryptographic methods include symmetric encryption, which is fast but requires secure key sharing, and asymmetric encryption, which offers secure key exchange but has higher computational overhead. Modern distributed systems increasingly adopt hybrid encryption techniques, combining the speed of symmetric algorithms such as AES with the secure key management capabilities of asymmetric algorithms like RSA and Elliptic Curve Cryptography (ECC). This approach provides stronger security, better scalability, and improved performance, making it suitable for cloud computing, IoT networks, big data, and distributed databases.

Several studies highlight the security challenges associated with cloud computing and IoT, including data leakage, unauthorized access, denial-of-service attacks, privacy concerns, limited computational resources of IoT devices, and the growing need for secure cloud storage. Hybrid encryption has emerged as an effective solution because it balances computational efficiency with strong cryptographic protection while supporting secure communication across heterogeneous network environments. Research also emphasizes the importance of robust key management, authentication, and secure data transmission for maintaining trust in distributed systems.

The paper explains that hybrid encryption techniques improve security, speed, scalability, reliability, and key management, making them widely applicable in cloud computing, edge computing, smart healthcare, military communication systems, distributed databases, and IoT applications. Ethical considerations are also emphasized, requiring encryption systems to protect user privacy, maintain data confidentiality and integrity, ensure responsible use of cryptographic technologies, and comply with legal and cybersecurity standards. Researchers are expected to design secure systems that safeguard personal, financial, medical, and government information while promoting digital trust and protecting human rights.

Finally, the paper highlights the significance of the International Conference on AI-Driven Data Science for Autonomous Systems (ICIADAS) in encouraging student research, fostering interdisciplinary collaboration, strengthening academia–industry partnerships, promoting ethical AI and cybersecurity research, and inspiring young researchers to develop secure, innovative, and socially responsible distributed computing technologies.

Conclusion

A new hybrid technique for data encryption in distributed computing systems provides an efficient and secure solution for protecting sensitive information in modern digital environments. The proposed approach combines the strengths of symmetric encryption, asymmetric encryption, and hashing techniques to achieve improved confidentiality, integrity, authentication, and secure key management. By integrating fast data encryption methods such as AES with secure key exchange algorithms like RSA or ECC and integrity verification using SHA-256, the system overcomes many limitations of traditional single-layer encryption techniques. The hybrid encryption model improves overall system performance by reducing computational complexity while maintaining strong protection against cyber threats including brute-force attacks, replay attacks, unauthorized access, and data tampering. The technique also enhances scalability and reliability in distributed environments such as cloud computing, IoT networks, distributed databases, healthcare systems, banking applications, and edge computing platforms.

Copyright

Copyright © 2026 Kajal Suresh Bagde, Prof. Bhagyashree Kumbhare, Prof. Yamini Laxane. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.