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In this research, we investigate an example of the Learning Parity with noise (LPN) problem, the hotel key lock problem, discussed by Dr. Robert Kubler [4]. He proposed a solution using the decision tree classification problem. Our research indicated that this approach did not provide solutions for secret key values larger than n = 24. A tweaking of the Decision Tree parameters did not yield further success, neither did the Naïve Bayes approach. We tried a novel approach where we attempted to solve the problem by finding a vector c where Ac ≈ B + e, by finding vector c where the difference between Ac and B + e was minimal. This approach showed promise and should be further pursued.

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Determining the Secret Key in Hotel Card Lock Key Communication

  • 会议论文

  • 发表日期：

    2025年

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  • Cheryl Hinds,
  • Jonathan Graham,
  • Thalia Guadalupe

摘要

In this research, we investigate an example of the Learning Parity with noise (LPN) problem, the hotel key lock problem, discussed by Dr. Robert Kubler [4]. He proposed a solution using the decision tree classification problem. Our research indicated that this approach did not provide solutions for secret key values larger than n = 24. A tweaking of the Decision Tree parameters did not yield further success, neither did the Naïve Bayes approach. We tried a novel approach where we attempted to solve the problem by finding a vector c where Ac ≈ B + e, by finding vector c where the difference between Ac and B + e was minimal. This approach showed promise and should be further pursued.