Securely Similarity Determination of Convex Geometry Graphics Under the Malicious Model

Liu, Xiaomeng; Liu, Xin

doi:10.1007/978-3-031-26193-0_36

Cited by 3 publications

(2 citation statements)

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“…Problem description: Assume that Alice owns the graphic G and the cloud platform stores the graphic H, and they judge whether the graphics of both parties are similar and match on the premise that the graphics information of each party is confidential. According to the transformation rule [27], convert the graphics into vectors, judge whether the vectors held by both sides are proportional (as shown in Figure 1), then judge whether the two graphics are similar. When the elements in the two groups of vectors are proportional, the two groups of vectors can be expressed linearly, which is shown in the geometric graphic that the two vectors must be collinear, that is, calculate the angle between the two vectors cos θ = X,Y…”

Section: Problem Description and Transformation Rulementioning

confidence: 99%

“…(θ is the angle between vector X and vector Y), when cos θ = ±1, θ is 0 or π, that is, the two vectors are collinear, then the two vectors are proportional, and the graphic is similar; otherwise, G and H are not similar, and the cloud platform continues to retrieve other graphics. Transformation rule: Both parties establish a coordinate system on their private graphics according to the rectangular coordinate system establishment rule [27]. According to the method shown in Figure 1, Alice can obtain vectors A 1 = (a 1 , a 2 , .…”

Section: X| |Y|mentioning

confidence: 99%

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AAJS: An Anti-Malicious Attack Graphic Similarity Judgment System in Cloud Computing Environments

Liu

Xiong

et al. 2023

Electronics

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With the rapid development of cloud computing and other modern technologies, collaborative computing between data is increasing, and privacy protection and secure multi-party computation are also attracting more attention. The emergence of cloud computing provides new options for data holders to perform complex computing problems and to store images; however, data privacy issues cannot be ignored. If a graphic is encrypted and stored in the cloud, the cloud server will perform confidential similar matching when the user searches. At present, most research on searchable encryption is focused on text search, with few schemes researched on how to finish the graphic search. To solve this problem, this paper proposes a secure search protocol based on graph shape under the semi-honest model. Using the cut-choose method and zero-knowledge proof, further designs of the anti-malicious attack graphic similarity judgment system (AAJS) based on the Paillier encryption algorithm, can achieve the secure search and matching of the graph while resisting malicious adversary attacks. The proposed protocol’s security is proved by the real/ideal model paradigm. This paper conducts performance analysis and experimental simulation on the existing scheme and the experiments demonstrate that the system achieves high execution efficiency.

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Section: Problem Description and Transformation Rulementioning

confidence: 99%

Section: X| |Y|mentioning

confidence: 99%