Secure forensic data transmission system in cloud database using fuzzy based butterfly optimization and modified ECC

Abstract

Data forensic is the investigation of digital data which illustrates how it is created and utilized. It is composed of detection, preservation, retrieval, and analyzing digital information. These data are stored in different domains. When storing the data in a cloud database it is ineluctable to circumvent the data leakage. Several deep learning approaches were conducted to resist data leakage. However, optimized security was not obtained. To address the aforementioned issues we have proposed a novel modified elliptic curve cryptography based secure forensic data transmission system (MESFDT) in the cloud database. The conventional ECC selects the keys used for the encryption and decryption process randomly. This might cause the generation of countless keys and can be easily hacked by a malicious user. Therefore we adopted fuzzy based butterfly optimization algorithm (FBOA) for the generation of keys. Thus the ECC is modified to form modified elliptic curve cryptography (MECC). The proposed method is comprised of a MECC integration unit, wireless transceiver, USB interface, MECC unit, smart card reader. This helps to transfer the forensic data from the user to the cloud database securely and also circumvent the duplication of data. The experimental study depicts that the proposed method increases the security of forensic data and mitigates the encryption and decryption time more gently than the other existing approaches.

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