Journal
| Title | Solving the Binary Puzzle with Genetic Algorithm Posted by Orven Llantos |
| Authors | Balagbis, Rachel Anne B. ; Llantos, Orven E. |
| Publication date | 2024/04/29 |
| Journal | Procedia Computer Science |
| Volume | 234 |
| Issue | C |
| Pages | 954-961 |
| Publisher | Elsevier B. V. |
| Abstract | The increased internet usage after the pandemic led the UN Forum to improve cybersecurity measures, with zero-knowledge proofs (ZKP) being a viable solution for securing confidential information. ZKP protocols can be demonstrated through the binary puzzle, an NP-complete logic puzzle with four specific constraints. The key contribution of this paper is its successful implementation of the genetic algorithm as a new method to solve the binary puzzle. The optimized fitness function determined the solution at an average of 1.33-2.33 generations for populations ranging from 100 to 500. Its quadratic property calculated the solution faster than the ordinary linear fitness function. |
| Index terms / Keywords | Zero-knowledge proof; Binary Puzzle; Genetic Algorithm; Artificial Intelligence; Fitness Function; NP-Complete |
| DOI | https://doi.org/10.1016/j.procs.2024.03.084 |
| URL | https://www.sciencedirect.com/science/article/pii/S1877050924004423 |