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<p>Cloud computing has become increasingly essential due to the growing demand for high-quality services at minimal cost; however, ensuring data security remains a critical challenge, particularly in key management within encrypted environments. This study addresses the problem of secure data access and key vulnerability in big data cloud frameworks by proposing a novel Artificial Algae XOR Deoxyribonucleic Cryptography (AAXORDC) model. The primary objective to enhance data confidentiality and optimize key management through an intelligent cryptographic mechanism. The proposed method integrates Artificial Algae Optimization for efficient key Generation, XOR-based Encryption for lightweight processing, and Deoxyribonucleic Acid (DNA)-based cryptographic encoding to strengthen security. The framework ensures secure key distribution by encrypting the secret key and sharing it only with authenticated users. Simulation results demonstrate the effectiveness of the proposed model, achieving an encryption time of 257 ms, decryption time of 464 ms, latency of 38 ms, throughput of 133 Mbps, and overall execution time of 32&#xa0;min. These results indicate improved efficiency and security compared to existing approaches. Therefore, the AAXORDC model provides a robust, scalable solution for secure access to big data in cloud computing environments.</p>

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Deep secure cloud of things accessing in big data framework using intelligent optimized crypto mechanism

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • S. Mary Evanchalin,
  • M. Anisha Vergin,
  • R. Ravi

摘要

Cloud computing has become increasingly essential due to the growing demand for high-quality services at minimal cost; however, ensuring data security remains a critical challenge, particularly in key management within encrypted environments. This study addresses the problem of secure data access and key vulnerability in big data cloud frameworks by proposing a novel Artificial Algae XOR Deoxyribonucleic Cryptography (AAXORDC) model. The primary objective to enhance data confidentiality and optimize key management through an intelligent cryptographic mechanism. The proposed method integrates Artificial Algae Optimization for efficient key Generation, XOR-based Encryption for lightweight processing, and Deoxyribonucleic Acid (DNA)-based cryptographic encoding to strengthen security. The framework ensures secure key distribution by encrypting the secret key and sharing it only with authenticated users. Simulation results demonstrate the effectiveness of the proposed model, achieving an encryption time of 257 ms, decryption time of 464 ms, latency of 38 ms, throughput of 133 Mbps, and overall execution time of 32 min. These results indicate improved efficiency and security compared to existing approaches. Therefore, the AAXORDC model provides a robust, scalable solution for secure access to big data in cloud computing environments.