Using Topological Data Analysis to classify Encrypted Bits

Authors: Jayati Kaushik, Aaruni Kaushik, Upasana Parashar
Published: 2023-01-18

Source: https://arxiv.org/abs/2301.07393

PDF: https://arxiv.org/pdf/2301.07393

AIにより推定されたラベル

機械学習 アルゴリズム設計 画像フォレンジック

※ こちらのラベルはAIによって自動的に追加されました。そのため、正確でないことがあります。
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Abstract

We present a way to apply topological data analysis for classifying encrypted bits into distinct classes. Persistent homology is applied to generate topological features of a point cloud obtained from sets of encryptions. We see that this machine learning pipeline is able to classify our data successfully where classical models of machine learning fail to perform the task. We also see that this pipeline works as a dimensionality reduction method making this approach to classify encrypted data a realistic method to classify the given encryptioned bits.