Hybridized Model for Data Security Based on Security Hash Analysis (SHA 512) and Salting Techniques

Abstract

High-profile security breaches and attacks on many organization’s database have been on the increase and the consequences of this, are the adverse effect on the organizations in terms of financial loss and reputation. Many of the security breaches has been ascribed to the vulnerability of the organization’s networks, security policy and operations. Additionally, the emerging technology solutions like Internet-ofThings (IoT), Artificial Intelligence, and Cloud Computing, has extremely exposed many of the organizations to different forms of cyber-threats and attacks. Researchers and system designers have made attempts to proffer solution to some of these challenges. However, the efficacy of the techniques remains a great concern due to insufficient control mechanisms. For instance, many of the techniques are majorly based on a single mode encryption techniques which are not too robust to withstand the threats and attacks on organization’s database. To proffer solution to these challenges, the current research designed and integrated a hybridized data security model based on Secured Hash Analysis (SHA 512) and Salting Techniques to enhance the adeptness of the existing techniques. The Hash Analysis algorithm was used to map the data considered to a bit string of a fixed length and salt was added to the password strings essentially to hide its real hash value. The idea of adding salt to the end of the password is basically to complicate the password cracking process. The hybridized model was implemented in Windows environment using python 3.7 IDE platform and tested on a dedicated Local Area Network (LAN) that was exposed to threats from both internal and external sources. The results from the test show that the model performed well in terms of efficiency and robustness to attacks. The performance of the new model recorded a high level of improvement over the existing techniques with a recital of 97.6%.