Malicious computation prevention protocol for secure multi-party computation

Mishra, Durgesh Kumar; Koria, Neha; Kapoor, Nikhil; Bahety, Ravish

doi:10.1109/tencon.2009.5395855

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…In order to realize a secure multi-party protocol using anonymization, Shukla et al [26] combined an asymmetric encryption scheme and it relies on the existence of a credible third party, but it is difficult to find a credible third party in practical. Secure multiparty computation protocol require higher safety at malicious model, in order to prevent the malicious adversary departing protocol breach security protocol, Mishra et al [27] extended the Encrytpo Random protocol to introduce multiple trusted third parties, such that the security of the data is further guaranteed, and an attempt is made to further strengthen the existing protocol, thereby paving the way for a safer multi-party computation process. For the practical application of SMPC, Naidu et al [28] combined cryptography and secure multi-party computation technology to create an electronic voting system, which has high research value and significance.…”

Section: Related Workmentioning

confidence: 99%

An Entropy-View Secure Multi-Party Computation Protocol Based on Semi-honest Model

Luo

chen

et al. 2022

Preprint

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Secure multi-party computation(SMPC) is an important research area in cryptography with many application scenarios, but there are still many problems to be solved. Aiming at security and fairness issues in SMPC, we consider that semi-honest participants are able to execute the protocol according to the specification, but there would be some additional malicious operations such as collusion and refuse to exchange information in the process of information interaction, which leads to deviations in the security and fairness of the protocol. To solve the above problems, we combine information entropy and mutual information to propose an n-round information exchange protocol, in which each participant broadcasts a relevant information value in each round without revealing additional information. The uncertainty of the correct result value is fuzzed by the interactive information in each round, and each participant cannot determine the correct result value until the end of the protocol, which effectively prevents malicious behavior and ensures the correct execution of the protocol. Security analysis and fairness analysis show that under the semi-honest model, our protocol guarantees the security and relative fairness of the output obtained by the participants after completing the protocol.

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Section: Related Workmentioning

confidence: 99%

An Entropy-View Secure Multi-Party Computation Protocol Based on Semi-honest Model

Luo

chen

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In order to realize a secure multiparty protocol using anonymization, Shukla and Sadashivappa (2014) combined an asymmetric encryption scheme, and it relies on the existence of a credible third party, but it is difficult to find a credible third party in practical. A secure multiparty computation protocol requires greater safety with malicious model, in order to prevent the malicious adversary from departing from protocol or breaching security protocol, Mishra, Koria, et al (2009) extended the Encrytpo_Random protocol to introduce multiple trusted third parties, such that the security of the data is further guaranteed and attempted to further strengthen the existing protocol, thereby paving the way for a safer multiparty computation process. For the practical application of SMPC, Naidu et al (2016) combined cryptography and secure multiparty computation technology to create an electronic voting system, which has high research value and significance.…”

Section: Introductionmentioning

confidence: 99%

An Entropy-View Secure Multiparty Computation Protocol Based on Semi-Honest Model

Luo

Chen

et al. 2022

Journal of Organizational and End User Computing

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Data interaction scenarios involving multiple parties in network communities have problems of trust, data security, and reliability of the parties, and secure multiparty computation(SMPC) can effectively solve these problems. To address the security and fairness issues of SMPC, this study considers that semi-honest participants can lead to deviations in the security and fairness of the protocol, and combines information entropy and mutual information to present an n-round information exchange protocol in which each participant broadcasts a relevant information value in each round without revealing other information. The uncertainty of the correct outcome value is blurred by the interaction information in each round, and each participant is not sure of the correct outcome value until the end of the protocol, which effectively prevents malicious behavior and ensures the correct execution of the protocol. Security and fairness analysis shows that our protocol guarantees the security and relative fairness of the output obtained by the participants after completing the protocol.

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