A basic procedure for transforming readable data into encoded forms is encryption, which ensures security when the right decryption keys are used. hadoop is susceptible to possible cyber-attacks because it lacks built...
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A basic procedure for transforming readable data into encoded forms is encryption, which ensures security when the right decryption keys are used. hadoop is susceptible to possible cyber-attacks because it lacks built-in security measures, even though it can effectively handle and store enormous datasets using the hadoop Distributed File System (HDFS). The increasing number of data breaches emphasizes how urgently creative encryption techniques are needed in cloud-based big data settings. This paper presents Adaptive Attribute-Based Honey encryption (AABHE), a state-of-the-art technique that combines honey encryption with Ciphertext-Policy Attribute-Based encryption (CP-ABE) to provide improved data security. Even if intercepted, AABHE makes sure that sensitive data cannot be accessed by unauthorized parties. With a focus on protecting huge files in HDFS, the suggested approach achieves 98% security robustness and 95% encryption efficiency, outperforming other encryption methods including Ciphertext-Policy Attribute-Based encryption (CP-ABE), Key-Policy Attribute-Based encryption (KB-ABE), and Advanced encryption Standard combined with Attribute-Based encryption (AES+ABE). By fixing hadoop’s security flaws, AABHE fortifies its protections against data breaches and enhances hadoop’s dependability as a platform for processing and storing massive amounts of data.
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