Smart Fine-Tuning of Target Key Generation for Trusted Counting-Based Secret Sharing

Internet usage is currently requiring sensitive information to be more secure, requesting different developing trusting techniques other than traditional target key single validation. Normal security methods are becoming not sufficient for protection, especially when multiple trusted users are required for accessing sensitive data simultaneously diverting individuality. Therefore, secret sharing came to place, allowing the secret target key to be reformed into isolated shares, to be distributed among participants for special recombination authentication whenever validation needed. Recently, counting-based secret sharing (CBSS) has been proposed as practical secret sharing scheme. CBSS strategy is built providing shares running specific counting strategy to reproduce back its main secret target key (TK) trustfully. This work focuses on CBSS target key generation directing to improve its original construction being practically trusted for securely safe process. The research applied its generation proposing adopting zeros differently and using possible pseudo-random number generation (PRNG) potential alterations, studying their fine-tuning features and remarking the resulting effects on overall scheme performance. The study experimented numerous different TKs smart selections sensing essential trust factors of security, number of users, and techno complexity. The exploration selected the effective TKs based on comparing and analyzing all results, as verified by contrasting all dissimilar priority factors. The remarks are showing attractive contribution of 61% improvement testing all procedures mixing their independent factors in a novel fair unified combination.