Enhancing Digital Forensics Security Involves the Implementation of a Robust Storage Framework that Employs AES Encryption alongside Efficient Key Generation Technique

Digital forensics is important in investigating cybercrimes and in proving the digital evidence. However, conventional forensic storage systems have defects such as data manipulation, unauthorized access, and unreliability of the system especially in cloud computing environment. In order to address these challenges, this paper proposes a Digital Forensic Architecture with Authentication and Optimal Key Generation Encryption (DFA-AOKGE) as a secure framework that is meant to enhance the security, integrity and credibility of forensic investigations. The DFA-AOKGE model performs the storage and transport of the forensic data in a blockchain-based architecture across different node to avoid the risks of a single point of failure. This way ensures that critical information is easily retrievable and nobody can alter the proof. Also, a Robust Block Verification System (RBVS) is proposed to validate the digital evidence, detect any attempt of alteration and sustain the information integrity throughout the investigation process. For enhancing the security, the model applies an Improved Equilibrium Optimizer (EEO) for generating cryptographic keys to make the encryption more effective against brute force attacks. Also, the MHE allows for operations on the encrypted forensic data without the need to decrypt the data, thus preserving the data’s privacy during the analysis process. As a result, the DFA-AOKGE integrates these sophisticated mechanisms to provide a comprehensive and secure digital forensic approach for the cloud computing environment where the threats such as hacking and data leakage are frequent.