A Secure Data Fragmentation Scheme Based on Pseudo-Entropy

Autor: Dan Liu, Weitao Lin, Wei Wang, Xin Wang, Qian Hu, Wanxin Hou
Rok vydání: 2022
DOI: 10.21203/rs.3.rs-2079788/v1
Popis: The typical fragmentation schemes divide the data into continuous segments, causing an uneven amount of information in the segments, resulting in a threat to the security of the overall scheme after obtaining part of the leaked information posed by an adversary with mighty computing power. To combat such attacks, we propose a pseudo-entropy-based fragmentation scheme (PEFS), which further reduces the probability of the adversaries predicting the remaining information from partially leaking information and can prevent the eavesdroppers from colluding to form a more powerful attack. Considering the current situation that fragmentation schemes lack a unified theoretical model, we proposed a data fragmentation security model, and its provable security is verified. At the same time, this paper establishes a set of security level evaluation methods for multi-channel data fragmentation transmission and demonstrates the effectiveness of the fragmentation level evaluation methods from a theoretical point of view. Further, we propose a fragmentation scheme evaluation algorithm, and through the comparison experiment with the traditional continuous fragmentation scheme shows that the fragmentation scheme based on pseudo-entropy has universality and superiority in actual transmission scenarios.
Databáze: OpenAIRE
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