A Simulation Software for Testing of Image Matching Algorithms in UAV Terrain-Aided Navigation

Grzywiński, Stanisław; Turek, Piotr; Bużantowicz, Witold

doi:10.1109/icmt52455.2021.9502773

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…In addition, secure computing geometry is widely used in the field of the positioning [19][20][21]. Among them, graphics retrieval technology is widely used in terrain matching [22], mechanical parts retrieval [23], biomolecular detection [24], face recognition [25], etc. So, it is particularly important to study the significance of secure judgment of graphic similarity.…”

Section: Introductionmentioning

confidence: 99%

The secure judgment of graphic similarity against malicious adversaries

Liu

et al. 2022

Preprint

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With the the advent era of big data, the secure computation calculates data on the premise of protecting data privacy, to realize the availability and invisibility of data. Secure multi-party computation, as one of three major technical tools of privacy computing, can still securely carry out data collaborative computation without a trusted third party. As an important branch of secure multi-party computation, the secure computing geometric problem can solve practical problems in the military, national defense, finance, life, and other fields, which has important research significance. In this paper, the graphic similarity problem is studied. Firstly, this paper proposes the adjacency matrix vector coding method of isomorphic graphics and uses the Paillier variant cryptosystem to securely solve the graphic similarity judgment under the semi-honest model. By using an elliptic curve cryptosystem and zero-knowledge proof to solve the possible malicious attacks under the semi-honest model, a graphic similarity judgment protocol under the malicious model is designed. The protocol can resist malicious attacks, has high computational efficiency, and has wide application value.

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Section: Introductionmentioning

confidence: 99%

The secure judgment of graphic similarity against malicious adversaries

Liu

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition, secure computing geometry is widely used in the field of the positioning [26][27][28] . Among them, graphics retrieval technology is widely used in terrain matching 29 , mechanical parts retrieval 30 , biomolecular detection 23,31 , face recognition 32,33 , etc. So, it is particularly important to study the significance of secure judgment of graphic similarity.…”

mentioning

confidence: 99%

The secure judgment of graphic similarity against malicious adversaries and its applications

Liu

Luo³

et al. 2023

Sci Rep

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With the advent of the era of big data, privacy computing analyzes and calculates data on the premise of protecting data privacy, to achieve data ‘available and invisible’. As an important branch of secure multi-party computation, the geometric problem can solve practical problems in the military, national defense, finance, life, and other fields, and has important research significance. In this paper, we study the similarity problem of geometric graphics. First, this paper proposes the adjacency matrix vector coding method of isomorphic graphics, and use the Paillier variant encryption cryptography to solve the problem of isomorphic graphics confidentiality under the semi-honest model. Using cryptography tools such as elliptic curve cryptosystem, zero-knowledge proof, and cut-choose method, this paper designs a graphic similarity security decision protocol that can resist malicious adversary attacks. The analysis shows that the protocol has high computational efficiency and has wide application value in terrain matching, mechanical parts, biomolecules, face recognition, and other fields.

show abstract

A Simulation Software for Testing of Image Matching Algorithms in UAV Terrain-Aided Navigation

Cited by 2 publications

References 13 publications

The secure judgment of graphic similarity against malicious adversaries

The secure judgment of graphic similarity against malicious adversaries

The secure judgment of graphic similarity against malicious adversaries and its applications

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