Name
Abstract | ||
|---|---|---|
In this paper, we ask a question whether evolutionary algorithms can evolve cryptographic algorithms when no precise design criteria are given. Our strategy utilizes Cartesian Genetic Programming in the bi-level optimization setting with multiple populations trying to evolve a cryptographic algorithm and break it. To challenge our design paradigm, we consider a number of scenarios with varying criteria on the system and its security. We are able to obtain interesting results in several scenarios where the attacker is not able to understand the text with more than a random chance. Interestingly, our system is able to develop various versions of one-time pads, which are the only systems that ensure perfect secrecy. Although our system is far from practical, we consider it interesting since it gives good results that are also human-readable.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3319619.3326869 | GECCO |
Keywords | DocType | ISBN |
Collection scheduling, simulation, genetic algorithm, deep neural networks | Conference | 978-1-4503-6748-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stjepan Picek | 1 | 164 | 44.70 |
| Karlo Knezevic | 2 | 9 | 0.83 |
| Domagoj Jakobovic | 3 | 195 | 29.01 |
| Ante Derek | 4 | 3 | 0.72 |