Literatura científica selecionada sobre o tema "Verifiable computing"
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Artigos de revistas sobre o assunto "Verifiable computing"
Simunic, Silvio, Dalen Bernaca e Kristijan Lenac. "Verifiable Computing Applications in Blockchain". IEEE Access 9 (2021): 156729–45. http://dx.doi.org/10.1109/access.2021.3129314.
Texto completo da fonteYan, Zheng, Xixun Yu e Wenxiu Ding. "Context-Aware Verifiable Cloud Computing". IEEE Access 5 (2017): 2211–27. http://dx.doi.org/10.1109/access.2017.2666839.
Texto completo da fonteSong, Beibei, Dehua Zhou, Jiahe Wu, Xiaowei Yuan, Yiming Zhu e Chuansheng Wang. "Protecting Function Privacy and Input Privacy in the Publicly Verifiable Outsourcing Computation of Polynomial Functions". Future Internet 15, n.º 4 (21 de abril de 2023): 152. http://dx.doi.org/10.3390/fi15040152.
Texto completo da fonteSun, Jiameng, Binrui Zhu, Jing Qin, Jiankun Hu e Qianhong Wu. "Confidentiality-Preserving Publicly Verifiable Computation". International Journal of Foundations of Computer Science 28, n.º 06 (setembro de 2017): 799–818. http://dx.doi.org/10.1142/s0129054117400196.
Texto completo da fonteYao, Shuang, e Dawei Zhang. "An Anonymous Verifiable Random Function with Applications in Blockchain". Wireless Communications and Mobile Computing 2022 (19 de abril de 2022): 1–12. http://dx.doi.org/10.1155/2022/6467866.
Texto completo da fonteJiao, Zi, Fucai Zhou, Qiang Wang e Jintong Sun. "RPVC: A Revocable Publicly Verifiable Computation Solution for Edge Computing". Sensors 22, n.º 11 (25 de maio de 2022): 4012. http://dx.doi.org/10.3390/s22114012.
Texto completo da fonteWang, Jianfeng, Xiaofeng Chen, Xinyi Huang, Ilsun You e Yang Xiang. "Verifiable Auditing for Outsourced Database in Cloud Computing". IEEE Transactions on Computers 64, n.º 11 (1 de novembro de 2015): 3293–303. http://dx.doi.org/10.1109/tc.2015.2401036.
Texto completo da fonteXu, Lingling, e Shaohua Tang. "Verifiable computation with access control in cloud computing". Journal of Supercomputing 69, n.º 2 (29 de outubro de 2013): 528–46. http://dx.doi.org/10.1007/s11227-013-1039-z.
Texto completo da fonteZhang, Kai, Lifei Wei, Xiangxue Li e Haifeng Qian. "Scalable and Soundness Verifiable Outsourcing Computation in Marine Mobile Computing". Wireless Communications and Mobile Computing 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/6128437.
Texto completo da fonteGheorghiu, Alexandru, Elham Kashefi e Petros Wallden. "Robustness and device independence of verifiable blind quantum computing". New Journal of Physics 17, n.º 8 (19 de agosto de 2015): 083040. http://dx.doi.org/10.1088/1367-2630/17/8/083040.
Texto completo da fonteTeses / dissertações sobre o assunto "Verifiable computing"
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.
Texto completo da fonteMachine Learning (ML) represents a new trend in science because of its power to solve problems automatically and its wide spectrum of applications (e.g., business, healthcare domain, etc.). This attractive technology caught our attention from a cryptography point of view in the sense that we worked during this Ph.D. to ensure secure usage of ML setups. Our Ph.D. work proposes a secure remote evaluation over different ML setups (for inference and for training). This thesis addresses two cornerstones: confidentiality of training or inference data and remote evaluation integrity in different ML setups (federated learning or transfer learning-based inference). In contrast, most other works focus only on data confidentiality. In our thesis, we proposed three architectures/frameworks to ensure a secure remote evaluation for the following ML setups: Neural Networks (NN), Federated Learning (FL), and Transfer Learning (TL). Particularly, our FL and TL architectures are the first that treat both the confidentiality and integrity security properties. We built these architectures using or modifying pre-existing VC schemes over homomorphic encrypted data: mainly we use VC protocols for BFV and Paillier schemes. An essential characteristic for our architectures is their generality, in the sense, if there are improvements in VC protocols and HE schemes, our frameworks can easily take into account these new approaches. This work opens up many perspectives, not only in privacy-preserving ML architectures, but also for the tools used to ensure the security properties. For example, one important perspective is to add differential privacy (DP) to our FL architecture
Sun, Wenhai. "Towards Secure Outsourced Data Services in the Public Cloud". Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/84396.
Texto completo da fontePh. D.
Azraoui, Monir. "Vérifiabilité et imputabilité dans le Cloud". Thesis, Paris, ENST, 2016. http://www.theses.fr/2016ENST0032/document.
Texto completo da fonteThis thesis proposes more efficient cryptographic protocols that enable cloud users to verify (i) the correct storage of outsourced data and (ii) the correct execution of outsourced computation. We first describe a cryptographic protocol that generates proofs of retrievability, which enable data owners to verify that the cloud correctly stores their data. We then detail three cryptographic schemes for verifiable computation by focusing on three operations frequent in data processing routines, namely polynomial evaluation, matrix multiplication and conjunctive keyword search. The security of our solutions is analyzed in the provable security framework and we also demonstrate their efficiency thanks to prototypes. We also introduce A-PPL, an accountability policy language that allows the expression of accountability obligations into machine-readable format. We expect our contributions to foster cloud adoption by organizations still wary of using this promising paradigm
Azraoui, Monir. "Vérifiabilité et imputabilité dans le Cloud". Electronic Thesis or Diss., Paris, ENST, 2016. http://www.theses.fr/2016ENST0032.
Texto completo da fonteThis thesis proposes more efficient cryptographic protocols that enable cloud users to verify (i) the correct storage of outsourced data and (ii) the correct execution of outsourced computation. We first describe a cryptographic protocol that generates proofs of retrievability, which enable data owners to verify that the cloud correctly stores their data. We then detail three cryptographic schemes for verifiable computation by focusing on three operations frequent in data processing routines, namely polynomial evaluation, matrix multiplication and conjunctive keyword search. The security of our solutions is analyzed in the provable security framework and we also demonstrate their efficiency thanks to prototypes. We also introduce A-PPL, an accountability policy language that allows the expression of accountability obligations into machine-readable format. We expect our contributions to foster cloud adoption by organizations still wary of using this promising paradigm
Rathi, Nilesh. "Scaling Blockchains Using Coding Theory and Verifiable Computing". Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5203.
Texto completo da fonteLivros sobre o assunto "Verifiable computing"
Demirel, Denise, Lucas Schabhüser e Johannes Buchmann. Privately and Publicly Verifiable Computing Techniques. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6.
Texto completo da fonteSchabhüser, Lucas, Johannes Buchmann e Denise Demirel. Privately and Publicly Verifiable Computing Techniques: A Survey. Springer International Publishing AG, 2017.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Verifiable computing"
Xu, Cheng, Ce Zhang e Jianliang Xu. "Verifiable Cloud Computing". In Encyclopedia of Wireless Networks, 1448–51. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_299.
Texto completo da fonteXu, Cheng, Ce Zhang e Jianliang Xu. "Verifiable Cloud Computing". In Encyclopedia of Wireless Networks, 1–4. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-32903-1_299-1.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Verifiable Computing for Specific Applications". In Privately and Publicly Verifiable Computing Techniques, 43–47. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_7.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Proof and Argument Based Verifiable Computing". In Privately and Publicly Verifiable Computing Techniques, 13–22. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_3.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Verifiable Computing from Fully Homomorphic Encryption". In Privately and Publicly Verifiable Computing Techniques, 23–25. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_4.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Verifiable Computing Frameworks from Functional Encryption and Functional Signatures". In Privately and Publicly Verifiable Computing Techniques, 37–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_6.
Texto completo da fonteMadi, Abbass, Renaud Sirdey e Oana Stan. "Computing Neural Networks with Homomorphic Encryption and Verifiable Computing". In Lecture Notes in Computer Science, 295–317. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61638-0_17.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Introduction". In Privately and Publicly Verifiable Computing Techniques, 1–3. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_1.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Preliminaries". In Privately and Publicly Verifiable Computing Techniques, 5–11. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_2.
Texto completo da fonteDemirel, Denise, Lucas Schabhüser e Johannes Buchmann. "Homomorphic Authenticators". In Privately and Publicly Verifiable Computing Techniques, 27–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53798-6_5.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Verifiable computing"
Fournet, Cedric, Chantal Keller e Vincent Laporte. "A Certified Compiler for Verifiable Computing". In 2016 IEEE 29th Computer Security Foundations Symposium (CSF). IEEE, 2016. http://dx.doi.org/10.1109/csf.2016.26.
Texto completo da fonteLiu, Shushu, e Zheng Yan. "Verifiable Edge Computing for Indoor Positioning". In ICC 2020 - 2020 IEEE International Conference on Communications (ICC). IEEE, 2020. http://dx.doi.org/10.1109/icc40277.2020.9148819.
Texto completo da fonteGennaro, Rosario. "Verifiable Outsourced Computation". In PODC '17: ACM Symposium on Principles of Distributed Computing. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3087801.3087872.
Texto completo da fonteHsu, Shuo-Fang, Yu-Jie Chang, Ran-Zan Wang, Yeuan-Kuen Lee e Shih-Yu Huang. "Verifiable Visual Cryptography". In 2012 Sixth International Conference on Genetic and Evolutionary Computing (ICGEC). IEEE, 2012. http://dx.doi.org/10.1109/icgec.2012.150.
Texto completo da fonteXiang, Tao, Weimin Zhang e Fei Chen. "A verifiable PSO algorithm in cloud computing". In 2014 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2014. http://dx.doi.org/10.1109/cec.2014.6900252.
Texto completo da fonteSekar, Vyas, e Petros Maniatis. "Verifiable resource accounting for cloud computing services". In the 3rd ACM workshop. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2046660.2046666.
Texto completo da fonteDolev, Shlomi, e Arseni Kalma. "Verifiable Computing Using Computation Fingerprints Within FHE". In 2021 IEEE 20th International Symposium on Network Computing and Applications (NCA). IEEE, 2021. http://dx.doi.org/10.1109/nca53618.2021.9685831.
Texto completo da fonteWen, Zhaocong, Jinman Luo, Huajun Chen, Jiaxiao Meng, Xuan Li e Jin Li. "A Verifiable Data Deduplication Scheme in Cloud Computing". In 2014 International Conference on Intelligent Networking and Collaborative Systems (INCoS). IEEE, 2014. http://dx.doi.org/10.1109/incos.2014.111.
Texto completo da fonteIslam, Mohammad Kamrul, e Ragib Hasan. "Verifiable Data Redundancy in the Cloud". In 2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom). IEEE, 2016. http://dx.doi.org/10.1109/bdcloud-socialcom-sustaincom.2016.16.
Texto completo da fonteChen, Yi-Hui, Ci-Wei Lan e Chiao-Chih Huang. "A Verifiable Visual Cryptography Scheme". In 2011 Fifth International Conference on Genetic and Evolutionary Computing (ICGEC). IEEE, 2011. http://dx.doi.org/10.1109/icgec.2011.53.
Texto completo da fonte