Adjusting counting-based secret-sharing via personalized passwords and email-authentic reliability
Adnan Gutub
Abstract
Counting-based secret-sharing (CBSS) is a current cybersecurity technique that provide applicable authentication for multi-participants collaborative trust access control utilization. The CBSS originally assigns its main confidential target key as secret random automatically selected to generate all participants private shares fulfilling trap-door function. CBSS is normally not allowing to entertain user preference in personalizing the passwords causing severe remembrance reliability difficulty. This research addressed this retention personalized challenge by adjusting the CBSS procedure commencing its process by user password selection choice, as for secret shares extraction to generate the target-key, securing the cybersecurity collaborative system. We proposed several algorithms for user-preference secret shares combination based on text and images alternatives, further verified by personal email convenience authentication. The proposals tested this adjusted CBSS reliability comparing overall security, systems number of shares possibilities, and variations functional time complexity as well as PSNR comparing to others for proper validation, noting its novel relevance attraction. The analysis remarked very interesting contribution comparison commented highest randomization secrecy of 95% for proposed model A passwords followed by 39%, 21%, 19% and 5%, for other different images-based passwords models B, C, D, and E, respectively. The work remarked attractive contribution compared to other works providing applicable CBSS real-life current utilization, opening door for promising progressive advancements to come.