Verifiable secure computation of linear fractional programming using certificate validation

Mohammed, Nedal M.; Sultan, Laman R.; Hamoud, Ahmed A.; Lomte, Santosh S.

doi:10.11591/ijpeds.v11.i1.pp284-290

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…Without proper security, a single malicious activity could compromise numerous websites. Cloud computingsecurity encompasses several challenges, including multi-tenancy, data loss [7] and leakage, ease of accessibility, identity management, unsafe APIs, inconsistencies in service level agreements, patch management, and internal threats. Enforcing security measures that provide to the diverse needs of all cloud users is challenging, as different users have varying security demands based on their objectives for using cloud services [8].…”

Section: Introductionmentioning

confidence: 99%

Effective privacy preserving in cloud computing using position aware Merkle tree model

Gangadharaiah,

Shrinivasacharya

2024

Bulletin EEI

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In this research manuscript, a new protocol is proposed for predicting the available space in the cloud and verifying the security of stored data. The protocol is utilized for learning the available data, and based on this learning, the available storage space is identified, after which the cloud service providers allow for data storage. The Integrity verification separates the private and the public data, which avoids privacy issues. The integration of the private data is done with the help of cloud service providers with respect to the third-party auditing (TPA). Earlier, public key cryptography and bilinear map technologies have been combined by the researchers, but the computation time and costs were high. To secure the integrity of the data storage, the client should execute several computations. Therefore, this research suggests a reliable and effective method called position-aware Merkle tree (PMT), which is implemented for ensuring data integrity. The proposed system uses a PMT that enables the TPA to perform multiple auditing tasks with high efficiency, less computational cost and computation time. Simulation results clearly shows that the developed PMT method consumed 0.00459 milliseconds of computation time, which is limited when compared to the existing models.

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Section: Introductionmentioning

confidence: 99%

Effective privacy preserving in cloud computing using position aware Merkle tree model

Gangadharaiah,

Shrinivasacharya

2024

Bulletin EEI

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“…Considering the challenge of solving large-scale LFP problems, Mohammed and Lomte [23] proposed a secure and verifiable scheme to offload the computations on the cloud side. Mohammed et al [24] also focused on outsourcing of scientific computations and shown how to use certificate validation to obtain correctness guarantees for privacypreserving outsourcing of LFP problem. Adding some parameters obtained by solving a linear fractional programming problem, [25] presented an extended version of the Tikhonov regularization method.…”

Section: Introductionmentioning

confidence: 99%

An exact iterative algorithm to solve a linear fractional programming problem

Köçken¹,

Özkök²,

Ahlatçıoğlu³

2022

Scientia Iranica

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The Linear Fractional Programming (LFP) problem that optimizes the ratio of two linear objective functions under linear constraints has a wide range of application areas. Based on the traditional definition of continuity, we developed an exact iterative algorithm that does not depend on big-M coefficients.Removing the nonlinearity in the fractional objective function by converting the objective function into a linear form, an equivalent linear-iterative problem is obtained and a computationally efficient algorithm is proposed. We also analyze the unbounded and asymptotic solution case of the LFP. To demonstrate the efficiency of the proposed method, illustrative numerical examples are provided for all solution cases. Also, we analyze the validity of our algorithm and compare our results with the existing algorithm from the literature by generating random large-scale test problems.

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“…Ghadle and Pathade [12] studied generalized hexagonal and octagonal fuzzy numbers by ranking method. Moreover, properties of the fuzzy transportation have been studied by several authors [13][14][15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

DA systematic approach for solving mixed constraint fuzzy balanced and unbalanced transportation problem

Hamoud

Ghadle

Pathade

2020

IJEECS

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<p>In the present article, a mixed type transportation problem is considered. Most of the transportation problems in real life situation have mixed type transportation problem this type of transportation problem cannot be solved by usual methods. Here we attempt a new concept of Best Candidate Method (BCM) to obtain the optimal solution. To determine the compromise solution of balanced mixed fuzzy transportation problem and unbalanced mixed fuzzy transportation problem of trapezoidal and trivial fuzzy numbers with new BCM solution procedure has been applied. The method is illustrated by the numerical examples.</p>

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Verifiable secure computation of linear fractional programming using certificate validation

Cited by 4 publications

References 21 publications

Effective privacy preserving in cloud computing using position aware Merkle tree model

Effective privacy preserving in cloud computing using position aware Merkle tree model

An exact iterative algorithm to solve a linear fractional programming problem

DA systematic approach for solving mixed constraint fuzzy balanced and unbalanced transportation problem

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