Relevant bibliographies by topics / Verifiable computing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Verifiable computing'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Verifiable computing"

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Simunic, Silvio, Dalen Bernaca, and Kristijan Lenac. "Verifiable Computing Applications in Blockchain." IEEE Access 9 (2021): 156729–45. http://dx.doi.org/10.1109/access.2021.3129314.

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Yan, Zheng, Xixun Yu, and Wenxiu Ding. "Context-Aware Verifiable Cloud Computing." IEEE Access 5 (2017): 2211–27. http://dx.doi.org/10.1109/access.2017.2666839.

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Jeveriya, Anjum Dr Shameem Akhter. "CONTEXT AWARE VERIFIABLE CLOUD COMPUTING." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 6 (2018): 33–56. https://doi.org/10.5281/zenodo.1336668.

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Cloud computing act as a significantpart for big data dispensation by providing statisticscalculating and treating facilities. Nevertheless, cloud facility breadwinners may spasm data confidentiality also offerimprecise data dispensation outcomes to operators, and hence cannot be completelyreliable. Contrariwise, inadequate by reckoning possessions and abilities, cloud users customarily cannot self-sufficientlyprocedure big data and accomplish authentication on the accuracy of data dispensation. This nurtures a distincttask on cloud computing authentication, exclusively when operator facts are
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Song, Beibei, Dehua Zhou, Jiahe Wu, Xiaowei Yuan, Yiming Zhu, and Chuansheng Wang. "Protecting Function Privacy and Input Privacy in the Publicly Verifiable Outsourcing Computation of Polynomial Functions." Future Internet 15, no. 4 (2023): 152. http://dx.doi.org/10.3390/fi15040152.

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With the prevalence of cloud computing, the outsourcing of computation has gained significant attention. Clients with limited computing power often outsource complex computing tasks to the cloud to save on computing resources and costs. In outsourcing the computation of functions, a function owner delegates a cloud server to perform the function’s computation on the input received from the user. There are three primary security concerns associated with this process: protecting function privacy for the function owner, protecting input privacy for the user and guaranteeing that the cloud server
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Sun, Jiameng, Binrui Zhu, Jing Qin, Jiankun Hu, and Qianhong Wu. "Confidentiality-Preserving Publicly Verifiable Computation." International Journal of Foundations of Computer Science 28, no. 06 (2017): 799–818. http://dx.doi.org/10.1142/s0129054117400196.

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Cloud computing enables users to outsource complicated computational tasks to a commercial computing server and relieves the users from establishing and maintaining expensive local computation systems. In this scenario, the minimum security requirement is that the result returned by the server must be correct. Publicly verifiable computation (PVC) has been proposed to address this issue by allowing the computational result to be publicly verifiable. Observing that computational tasks are usually private business in practice, we propose a confidentiality-preserving security tool referred to as
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Yao, Shuang, and Dawei Zhang. "An Anonymous Verifiable Random Function with Applications in Blockchain." Wireless Communications and Mobile Computing 2022 (April 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/6467866.

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Verifiable random function is a powerful function that provides a noninteractively public verifiable proof for its output. Recently, verifiable random function has found essential applications in designing secure consensus protocols in blockchain. How to construct secure and practical verifiable random functions has also attracted more and more attention. In this paper, we propose a practical anonymous verifiable random function. Security proofs show that the proposed anonymous verifiable random function achieves correctness, anonymity, uniqueness, and pseudorandomness. In addition, we show a
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Zara, Maham, Shuzhen Wang, and Hasan Ul Moin. "Blockchain-Based Verifiable Computation: A Review." Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences 61, no. 2 (2024): 113–28. http://dx.doi.org/10.53560/ppasa(61-2)850.

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Verifiable computation has been studied as a way to verify the outcomes of an outsourced computation. It is usually seen from the view of a user who wishes to outsource computation to a centralized third party but wants to ensure that the party provides correct results. With the said scheme, the verifier requests the prover to perform the computational task and then verifies the outcome by checking the output and the proof obtained from the prover. However, there are several security challenges within a centralized third party to execute verification tasks. Recently, the advancement in blockch
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Jiao, Zi, Fucai Zhou, Qiang Wang, and Jintong Sun. "RPVC: A Revocable Publicly Verifiable Computation Solution for Edge Computing." Sensors 22, no. 11 (2022): 4012. http://dx.doi.org/10.3390/s22114012.

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With publicly verifiable computation (PVC) development, users with limited resources prefer to outsource computing tasks to cloud servers. However, existing PVC schemes are mainly proposed for cloud computing scenarios, which brings bandwidth consumption or network delay of IoT devices in edge computing. In addition, dishonest edge servers may reduce resource utilization by returning unreliable results. Therefore, we propose a revocable publicly verifiable computation(RPVC) scheme for edge computing. On the one hand, RPVC ensures that users can verify the correct results at a small cost. On th
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Wang, Jianfeng, Xiaofeng Chen, Xinyi Huang, Ilsun You, and Yang Xiang. "Verifiable Auditing for Outsourced Database in Cloud Computing." IEEE Transactions on Computers 64, no. 11 (2015): 3293–303. http://dx.doi.org/10.1109/tc.2015.2401036.

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Xu, Lingling, and Shaohua Tang. "Verifiable computation with access control in cloud computing." Journal of Supercomputing 69, no. 2 (2013): 528–46. http://dx.doi.org/10.1007/s11227-013-1039-z.

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Dissertations / Theses on the topic "Verifiable computing"

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Madi, Abbass. "Secure Machine Learning by means of Homomorphic Encryption and Verifiable Computing." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG019.

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L’apprentissage automatique (ou le Machine Learning) est un domaine scientifique très en vogue en raison de sa capacité à résoudre les problèmes automatiquement et de son large spectre d’applications (par exemple, le domaine de la finance, le domaine médical, etc.). Les techniques de Machine Learning (ML) ont attiré mon attention du point de vue cryptographique dans le sens où les travaux de ma thèse ont eu comme objectif une utilisation sécurisée des méthodes de ML. Cette thèse traite l'utilisation sécurisée des techniques de ML sous deux volets : la confidentialité des données d’apprentissag
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Sun, Wenhai. "Towards Secure Outsourced Data Services in the Public Cloud." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/84396.

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Past few years have witnessed a dramatic shift for IT infrastructures from a self-sustained model to a centralized and multi-tenant elastic computing paradigm -- Cloud Computing, which significantly reshapes the landscape of existing data utilization services. In truth, public cloud service providers (CSPs), e.g. Google, Amazon, offer us unprecedented benefits, such as ubiquitous and flexible access, considerable capital expenditure savings and on-demand resource allocation. Cloud has become the virtual ``brain" as well to support and propel many important applications and system designs, for
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Azraoui, Monir. "Vérifiabilité et imputabilité dans le Cloud." Thesis, Paris, ENST, 2016. http://www.theses.fr/2016ENST0032/document.

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Cette thèse propose de nouveaux protocoles cryptographiques, plus efficaces que l’existant, et qui permettent aux utilisateurs du nuage informatique (le cloud) de vérifier (i) la bonne conservation des données externalisées et (ii) l'exécution correcte de calculs externalisés. Nous décrivons d'abord un protocole cryptographique qui génère des preuves de récupérabilité, qui permettent aux propriétaires de données de vérifier que le cloud stocke leurs données correctement. Nous détaillons ensuite trois schémas cryptographiques pour vérifier l’exactitude des calculs externalisés en se focalisant
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Azraoui, Monir. "Vérifiabilité et imputabilité dans le Cloud." Electronic Thesis or Diss., Paris, ENST, 2016. http://www.theses.fr/2016ENST0032.

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Cette thèse propose de nouveaux protocoles cryptographiques, plus efficaces que l’existant, et qui permettent aux utilisateurs du nuage informatique (le cloud) de vérifier (i) la bonne conservation des données externalisées et (ii) l'exécution correcte de calculs externalisés. Nous décrivons d'abord un protocole cryptographique qui génère des preuves de récupérabilité, qui permettent aux propriétaires de données de vérifier que le cloud stocke leurs données correctement. Nous détaillons ensuite trois schémas cryptographiques pour vérifier l’exactitude des calculs externalisés en se focalisant
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Rathi, Nilesh. "Scaling Blockchains Using Coding Theory and Verifiable Computing." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5203.

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The issue of scalability has been restricting blockchain from its widespread adoption. The current transaction rate of bitcoin is around seven transactions/second while its size has crossed the 300 GB mark. Although many approaches propose different ways to scale blockchain, e.g., sharding, lightning network, etc., we focus our analysis on methods utilizing ideas from coding theory. We first consider SeF, a blockchain archiving architecture utilizing LT codes to reduce storage constraints per node up to 1000x. SeF enables full nodes to store only a small number of encoded blocks or dropl
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Books on the topic "Verifiable computing"

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6.

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Schabhüser, Lucas, Johannes Buchmann, and Denise Demirel. Privately and Publicly Verifiable Computing Techniques: A Survey. Springer International Publishing AG, 2017.

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Book chapters on the topic "Verifiable computing"

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Xu, Cheng, Ce Zhang, and Jianliang Xu. "Verifiable Cloud Computing." In Encyclopedia of Wireless Networks. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_299.

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Xu, Cheng, Ce Zhang, and Jianliang Xu. "Verifiable Cloud Computing." In Encyclopedia of Wireless Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-32903-1_299-1.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Verifiable Computing for Specific Applications." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_7.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Proof and Argument Based Verifiable Computing." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_3.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Verifiable Computing from Fully Homomorphic Encryption." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_4.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Verifiable Computing Frameworks from Functional Encryption and Functional Signatures." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_6.

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Madi, Abbass, Renaud Sirdey, and Oana Stan. "Computing Neural Networks with Homomorphic Encryption and Verifiable Computing." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61638-0_17.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Introduction." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_1.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Preliminaries." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_2.

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Demirel, Denise, Lucas Schabhüser, and Johannes Buchmann. "Homomorphic Authenticators." In Privately and Publicly Verifiable Computing Techniques. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_5.

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Conference papers on the topic "Verifiable computing"

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Pei, Xintao, Yuling Chen, Yun Luo, Zaidong Li, and Jianqi Wei. "Lightweight IoT-Oriented Verifiable Computing Scheme in Cloud Computing Circumstance." In 2024 IEEE Cyber Science and Technology Congress (CyberSciTech). IEEE, 2024. https://doi.org/10.1109/cyberscitech64112.2024.00017.

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Mazzocca, Carlo, Stefano Allevi, and Rebecca Montanari. "Certifying IoT Data with Verifiable Credentials." In 2024 22nd International Symposium on Network Computing and Applications (NCA). IEEE, 2024. https://doi.org/10.1109/nca61908.2024.00022.

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Xu, Ye, and Takashi Nishide. "Verifiable Homomorphic Secret Sharing for SIMD Operations." In 2024 Twelfth International Symposium on Computing and Networking Workshops (CANDARW). IEEE, 2024. https://doi.org/10.1109/candarw64572.2024.00058.

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Xiong, Keqi, Zehua Liu, Jiayong Wei, and Huimin Gong. "A Blockchain-Based Verifiable Data Quality Assessment Scheme." In 2025 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2025. https://doi.org/10.1109/iwcmc65282.2025.11059446.

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Tabaeiaghdaei, Seyedali, Filippo Costa, Jonghoon Kwon, Patrick Bamert, Yih-Chun Hu, and Adrian Perrig. "Debuglet: Programmable and Verifiable Inter-Domain Network Telemetry." In 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS). IEEE, 2024. http://dx.doi.org/10.1109/icdcs60910.2024.00032.

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Castellano, Dario, Roberto De Prisco, and Pompeo Faruolo. "Login System for OpenID Connect with Verifiable Credentials." In 2024 22nd International Symposium on Network Computing and Applications (NCA). IEEE, 2024. https://doi.org/10.1109/nca61908.2024.00027.

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Wang, Yalan, Liqun Chen, Long Meng, and Christopher J. P. Newton. "VCaDID: Verifiable Credentials with Anonymous Decentralized Identities." In 2024 IEEE 23rd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2024. https://doi.org/10.1109/trustcom63139.2024.00086.

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Zhang, Chi, Peng Jiang, Zijian Zhang, and Liehuang Zhu. "Verifiable Predicate-based Access Control Encryption with Dynamic Revocation." In 2025 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2025. https://doi.org/10.1109/iwcmc65282.2025.11059613.

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Liu, Shaojie, Hongbo Zhao, and Han Liu. "Demo: Specy Network - Trusted Multichain Automation with Verifiable Specifications." In 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS). IEEE, 2024. http://dx.doi.org/10.1109/icdcs60910.2024.00134.

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Shaik, Matheen Basha, and Roopa Vishwanathan. "Verifiable Computation in Smart Grids Using Dynamic Slicing." In 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2025. https://doi.org/10.1109/percomworkshops65533.2025.00101.

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Journal articles
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