Adaptive Serial Cascaded Deep Network-based Data Deduplication Mechanism with Hyper-Elliptic Curve Cryptography for Encryption in Cloud Environment
Keywords:
Data Deduplication; Cloud Environment; Optimized Serial Cascaded Deep Network; Enhanced Red-Tailed Hawk algorithm; Hyper-Elliptic Curve Cryptography with Optimal Key.Abstract
Cloud storage services utilize deduplication to optimize capacity and minimize bandwidth demands. This process efficiently reduces redundant data to a single instance, thereby conserving storage space. Deduplication is particularly effective when multiple users upload identical information to the cloud. However, deduplication poses challenges related to security and copyright issues. Implementing secure deduplication can significantly cut down on both storage and communication costs in cloud services, making it highly relevant in the era of big data. Systems that verify the proof-of-ownership allow individuals who have uploaded the same data to credibly assert their ownership to the cloud service. However, the common practice of encrypting data before uploading it for privacy reasons complicates deduplication efforts because encryption introduces randomness that prevents identifying duplicates. To overcome this, various schemes have been introduced that permit users to encrypt data with a common key for identical data sets. Nevertheless, many of these schemes are susceptible to security flaws, particularly not addressing the frequent changes in data ownership in a dynamic cloud storage environment. Therefore, creating a secure data deduplication model that overcomes the limitations of current approaches is essential. The implemented framework consists of data collection, deduplication phase and encryption. Initially, attributes likes “filename, size, block name, size, file-type hash tag, file location, file updated date and data pattern” are used for the deduplication process. Next, the collected data is provided as the input to the Optimized Serial Cascaded Deep Network (OSCDN)-based data deduplication model, which is the fusion of “Deep Belief Network (DBN) with Dilated Convolution Long Short Term Memory (DConv-LSTM)”, Here the parameters of OSCDN is tuned using “Enhanced Red-Tailed Hawk algorithm (ERTH)”. Further, the de-duplicated data is encrypted using “Hyper-Elliptic Curve Cryptography with Optimal Key (HECC-OK)”. In this setup, the ERTH algorithm selects keys in the most optimal manner. Subsequently, the encrypted data is stored on the cloud platform. The developed architecture then undergoes several experimental validations to showcase its enhanced performance rate relative to traditional deduplication methods.
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