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Thematische Bibliographien / Verifiable computing / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Verifiable computing“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

Zuletzt aktualisiert am 31. Juli 2025

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1

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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3

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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10

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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Zhang, Kai, Lifei Wei, Xiangxue Li, and 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.

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Outsourcing computation with verifiability is a merging notion in cloud computing, which enables lightweight clients to outsource costly computation tasks to the cloud and efficiently check the correctness of the result in the end. This advanced notion is more important in marine mobile computing since the oceangoing vessels are usually constrained with less storage and computation resources. In such a scenario, vessels always firstly outsource data set and perform a function computing over them or at first outsource computing functions and input data set into them. However, vessels may choose

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Xu, Qingshan, Xiaoqing Tan, and Rui Huang. "Improved Resource State for Verifiable Blind Quantum Computation." Entropy 22, no. 9 (2020): 996. http://dx.doi.org/10.3390/e22090996.

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Recent advances in theoretical and experimental quantum computing raise the problem of verifying the outcome of these quantum computations. The recent verification protocols using blind quantum computing are fruitful for addressing this problem. Unfortunately, all known schemes have relatively high overhead. Here we present a novel construction for the resource state of verifiable blind quantum computation. This approach achieves a better verifiability of 0.866 in the case of classical output. In addition, the number of required qubits is 2N+4cN, where N and c are the number of vertices and th

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Gheorghiu, Alexandru, Elham Kashefi, and Petros Wallden. "Robustness and device independence of verifiable blind quantum computing." New Journal of Physics 17, no. 8 (2015): 083040. http://dx.doi.org/10.1088/1367-2630/17/8/083040.

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Zhu, Yixiao, Hui Li, Jiangtao Cui, and Yong Ma. "Verifiable Subgraph Matching With Cryptographic Accumulators in Cloud Computing." IEEE Access 7 (2019): 169636–45. http://dx.doi.org/10.1109/access.2019.2955243.

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Ausekar, Swapnil Ramesh, and Syam Kumar Pasupuleti. "Dynamic Verifiable Outsourced Database with Freshness in Cloud Computing." Procedia Computer Science 143 (2018): 367–77. http://dx.doi.org/10.1016/j.procs.2018.10.408.

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Su, Yaping, Jianfeng Wang, Yunling Wang, and Meixia Miao. "Efficient Verifiable Multi-Key Searchable Encryption in Cloud Computing." IEEE Access 7 (2019): 141352–62. http://dx.doi.org/10.1109/access.2019.2943971.

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EL-YAHYAOUI, Ahmed, and Mohamed Dafir ECH-CHERIF EL KETTANI. "A Verifiable Fully Homomorphic Encryption Scheme for Cloud Computing Security." Technologies 7, no. 1 (2019): 21. http://dx.doi.org/10.3390/technologies7010021.

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Performing smart computations in a context of cloud computing and big data is highly appreciated today. It allows customers to fully benefit from cloud computing capacities (such as processing or storage) without losing confidentiality of sensitive data. Fully homomorphic encryption (FHE) is a smart category of encryption schemes that enables working with the data in its encrypted form. It permits us to preserve confidentiality of our sensible data and to benefit from cloud computing capabilities. While FHE is combined with verifiable computation, it offers efficient procedures for outsourcing

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wu, Junhua, Wenzhen Feng, Guopeng Liang, Tiantian Wang, Guangshun Li, and Yuanwang Zheng. "A Privacy Protection Scheme for Facial Recognition and Resolution Based on Edge Computing." Security and Communication Networks 2022 (March 10, 2022): 1–12. http://dx.doi.org/10.1155/2022/4095427.

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Facial recognition and resolution technology have extensive application scenarios in the era of big data. It ensures the consistency of personal identity in physical space and cyberspace by establishing correspondence between physical objects and network entities. However, massive data brings huge processing pressure to cloud service, and there are data leakage risks about personal information. To address this problem, we propose a privacy security protection scheme for facial recognition and resolution based on edge computing. Firstly, a facial recognition and resolution framework based on ed

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Nedal, M. Mohammed, R. Sultan Laman, A. Hamoud Ahmed, and S. Lomte Santosh. "Verifiable secure computation of linear fractional programming using certificate validation." International Journal of Power Electronics and Drive System (IJPEDS) 11, no. 1 (2020): 284–90. https://doi.org/10.11591/ijpeds.v11.i1.pp284-290.

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Outsourcing of scientific computations is attracting increasing attention since it enables the customers with limited computing resource and storage devices to outsource the sophisticated computation workloads into powerful service providers. However, it also comes up with some security and privacy concerns and challenges, such as the input and output privacy of the customers, and cheating behaviors of the cloud. Motivated by these issues, this paper focused on privacy-preserving Linear Fractional Programming (LFP) as a typical and practically relevant case for verifiable secure multiparty com

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Li, Cheng, Li Yang, and Jianfeng Ma. "A Secure and Verifiable Outsourcing Scheme for Assisting Mobile Device Training Machine Learning Model." Wireless Communications and Mobile Computing 2020 (November 17, 2020): 1–16. http://dx.doi.org/10.1155/2020/8825623.

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In smart applications such as smart medical equipment, more data needs to be processed and trained locally and near the local end to prevent privacy leaks. However, the storage and computing capabilities of smart devices are limited, so some computing tasks need to be outsourced; concurrently, the prevention of malicious nodes from accessing user data during outsourcing computing is required. Therefore, this paper proposes EVPP (efficient, verifiable, and privacy-preserving), which is a computing outsourcing scheme used in the training process of machine learning models. The edge nodes outsour

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Fu, Moxuan, Chuan Zhang, Chenfei Hu, Tong Wu, Jinyang Dong, and Liehuang Zhu. "Achieving Verifiable Decision Tree Prediction on Hybrid Blockchains." Entropy 25, no. 7 (2023): 1058. http://dx.doi.org/10.3390/e25071058.

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Machine learning has become increasingly popular in academic and industrial communities and has been widely implemented in various online applications due to its powerful ability to analyze and use data. Among all the machine learning models, decision tree models stand out due to their great interpretability and simplicity, and have been implemented in cloud computing services for various purposes. Despite its great success, the integrity issue of online decision tree prediction is a growing concern. The correctness and consistency of decision tree predictions in cloud computing systems need m

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Niu, Kun, Changgen Peng, Weijie Tan, Zhou Zhou, and Yi Xu. "Verifiable Location-Encrypted Spatial Aggregation Computing for Mobile Crowd Sensing." Security and Communication Networks 2021 (April 28, 2021): 1–11. http://dx.doi.org/10.1155/2021/6654539.

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Benefiting from the development of smart urban computing, the mobile crowd sensing (MCS) network has emerged as momentous communication technology to sense and collect data. The users upload data for specific sensing tasks, and the server completes the aggregation analysis and submits to the sensing platform. However, users’ privacy may be disclosed, and aggregate results may be unreliable. Those are challenges in the trust computation and privacy protection, especially for sensitive data aggregation with spatial information. To address these problems, a verifiable location-encrypted spatial a

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Zhu, Yixiao, Wenjie Ma, Jiangtao Cui, Xiaofang Xia, Yanguo Peng, and Jianting Ning. "PvCT: A Publicly Verifiable Contact Tracing Algorithm in Cloud Computing." Security and Communication Networks 2021 (May 28, 2021): 1–18. http://dx.doi.org/10.1155/2021/5514137.

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Contact tracing is a critical tool in containing epidemics such as COVID-19. Researchers have carried out a lot of work on contact tracing. However, almost all of the existing works assume that their clients and authorities have large storage space and powerful computation capability and clients can implement contact tracing on their own mobile devices such as mobile phones, tablet computers, and wearable computers. With the widespread outbreaks of the epidemics, these approaches are of less robustness to a larger scale of datasets when it comes to resource-constrained clients. To address this

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Ruiting, SHAN, CHEN Xiubo, XU Gang, et al. "Verifiable Multi‐Party Universal Blind Quantum Computing in Distributed Networks." Chinese Journal of Electronics 30, no. 4 (2021): 712–18. http://dx.doi.org/10.1049/cje.2021.05.013.

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Shen, Jian, Dengzhi Liu, Md Zakirul Alam Bhuiyan, Jun Shen, Xingming Sun, and Aniello Castiglione. "Secure Verifiable Database Supporting Efficient Dynamic Operations in Cloud Computing." IEEE Transactions on Emerging Topics in Computing 8, no. 2 (2020): 280–90. http://dx.doi.org/10.1109/tetc.2017.2776402.

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Premnath, Sriram N., and Zygmunt J. Haas. "A Practical, Secure, and Verifiable Cloud Computing for Mobile Systems." Procedia Computer Science 34 (2014): 474–83. http://dx.doi.org/10.1016/j.procs.2014.07.033.

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Wang, Hao, Debiao He, Jian Shen, Zhihua Zheng, Chuan Zhao, and Minghao Zhao. "Verifiable outsourced ciphertext-policy attribute-based encryption in cloud computing." Soft Computing 21, no. 24 (2016): 7325–35. http://dx.doi.org/10.1007/s00500-016-2271-2.

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Li, Jianwei, Xiaoming Wang, and Qingqing Gan. "Verifiable Data Search with Fine-Grained Authorization in Edge Computing." Security and Communication Networks 2022 (November 10, 2022): 1–15. http://dx.doi.org/10.1155/2022/4252466.

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In the research of searchable encryption, fine-grained data authorization is a convenient way to manage the search rights for users. Recently, Liu et al. proposed a fine-grained searchable scheme with verification, which can control the search authorization and verify the results. In this paper, we first present a forgery attack against Liu et al.’s scheme and then propose a novel scheme of verifiable data search with fine-grained authorization in edge environment. Based on the key aggregate mechanism and Merkle hash tree, our proposed scheme not only achieves file-oriented search permission m

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S, Aswin, Chandru V, Mathan Raj, and K. Ashok Kumar. "Secure Date Storage Using ECC Encryption with Verifiable Data Sharing in Cloud." International Research Journal of Computer Science 11, no. 04 (2024): 230–33. http://dx.doi.org/10.26562/irjcs.2024.v1104.16.

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Cloud data storage has become increasingly popular, but the security and privacy of data stored in the cloud remain major concerns. Cloud computing is the most feasible approach for implementing Digital Twin services since it has prodigious advantages. It provides on demand services, computing resources, ubiquitous network access, etc., making it suitable for the next-generation information technology architecture. In cloud-assisted data storage environments, the data owners generate data from physical assets and disseminate it to the cloud server.

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Zhang, Tao, Xiongfei Song, Lele Zheng, Yani Han, Kai Zhang, and Qi Li. "Towards Time-Sensitive and Verifiable Data Aggregation for Mobile Crowdsensing." Security and Communication Networks 2021 (January 22, 2021): 1–14. http://dx.doi.org/10.1155/2021/6679157.

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Mobile crowdsensing systems use the extraction of valuable information from the data aggregation results of large-scale IoT devices to provide users with personalized services. Mobile crowdsensing combined with edge computing can improve service response speed, security, and reliability. However, previous research on data aggregation paid little attention to data verifiability and time sensitivity. In addition, existing edge-assisted data aggregation schemes do not support access control of large-scale devices. In this study, we propose a time-sensitive and verifiable data aggregation scheme (

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G, Kulkarni Vaibhav. "Secure Integrity Auditing System for Electronic Patient Health Records using Advanced Encryption Techniques." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1536–38. http://dx.doi.org/10.22214/ijraset.2022.40089.

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Abstract: Cloud computing is one of evolving technology nowadays, giving versatile services. However, secure information sharing is vulnerable to cloud computing. With cloud storage services, users can remotely keep their information to the cloud and recognize the data sharing with others. Electronic wellbeing record (EHR) is a framework that gathers patients' computerized wellbeing data and offers it with other medical care suppliers in the cloud. Since EHR contains a lot of critical and delicate data about patients, it is necessitated that the framework guarantees reaction accuracy and capac

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Wang, Jianfeng, Hua Ma, Qiang Tang, et al. "Efficient verifiable fuzzy keyword search over encrypted data in cloud computing." Computer Science and Information Systems 10, no. 2 (2013): 667–84. http://dx.doi.org/10.2298/csis121104028w.

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As cloud computing becomes prevalent, more and more sensitive data is being centralized into the cloud by users. To maintain the confidentiality of sensitive user data against untrusted servers, the data should be encrypted before they are uploaded. However, this raises a new challenge for performing search over the encrypted data efficiently. Although the existing searchable encryption schemes allow a user to search the encrypted data with confidentiality, these solutions cannot support the verifiability of searching result. We argue that a cloud server may be selfish in order to save its com

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Mohammed, Nedal, Laman R. Sultan, and Santosh Lomte. "Privacy preserving outsourcing algorithm for two-point linear boundary value problems." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (2019): 1065. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp1065-1069.

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<p>One of a powerful application in the age of cloud computing is the outsourcing of scientific computations to cloud computing which makes cloud computing a very powerful computing paradigm, where the customers with limited computing resource and storage devices can outsource the sophisticated computation workloads into powerful service providers. One of scientific computations problem is Two-Point Boundary Value Problems(BVP) is a basic engineering and scientific problem, which has application in various domains. In this paper, we propose a privacy-preserving, verifiable and efficient

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Jayalakshmi, Karemallaiah, and Revaiah Prabha. "Verifiable data distribution technique for multiple applicants in a cloud computing ecosystem." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 1241–49. https://doi.org/10.11591/ijai.v13.i2.pp1241-1249.

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Cloud computing is the most exploited research technology in both industry and academia due to wide application and increases in adoption from global organizations. In cloud, computing data storage is one of the primary resources offered through cloud computing, however, an increase in participants raises major security concerns, as the user has no hold over the data. Furthermore, recent research has shown great potential for efficient data sharing with multiple participants. Existing researches suggest complicated and inefficient cloud security architecture. Hence, this research work proposes

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Chang, Ya-Fen. "Flexible Access Control over Verifiable Cloud Computing Services with Provable Security." Informatica 26, no. 2 (2015): 181–98. http://dx.doi.org/10.15388/informatica.2015.44.

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Park, Ki-Woong, Jaesun Han, JaeWoong Chung, and Kyu Ho Park. "THEMIS: A Mutually Verifiable Billing System for the Cloud Computing Environment." IEEE Transactions on Services Computing 6, no. 3 (2013): 300–313. http://dx.doi.org/10.1109/tsc.2012.1.

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Zhang, Xiaoyu, Xiaofeng Chen, Jianfeng Wang, Zhihui Zhan, and Jin Li. "Verifiable privacy-preserving single-layer perceptron training scheme in cloud computing." Soft Computing 22, no. 23 (2018): 7719–32. http://dx.doi.org/10.1007/s00500-018-3233-7.

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Karemallaiah, Jayalakshmi, and Prabha Revaiah. "Verifiable data distribution technique for multiple applicants in a cloud computing ecosystem." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 1241. http://dx.doi.org/10.11591/ijai.v13.i2.pp1241-1249.

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<span lang="EN-US"><span lang="EN-US">Cloud computing is the most exploited research technology in both industry and academia due to wide application and increases in adoption from global organizations. In cloud, computing data storage is one of the primary resources offered through cloud computing, however, an increase in participants raises major security concerns, as the user has no hold over the data. Furthermore, recent research has shown great potential for efficient data sharing with multiple participants. Existing researches suggest complicated and inefficient cloud securit

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Wu, Hongfeng, and Jingjing Yan. "Outsourcing Computing of Large Matrix Jordan Decomposition." Mathematical Problems in Engineering 2019 (August 19, 2019): 1–7. http://dx.doi.org/10.1155/2019/6410626.

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The Jordan decomposition of matrix is a typical scientific and engineering computational task, but such computation involves enormous computing resources for large matrices, which is burdensome for the resource-limited clients. Cloud computing enables computational resource-limited clients to economically outsource such problems to the cloud server. However, outsourcing Jordan decomposition of large-scale matrix to the cloud brings great security concerns and challenges since the matrices usually contain sensitive information. In this paper, we present a secure, verifiable, efficient, and priv

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El-Yahyaoui, Ahmed, and Mohamed Daifr Ech-Cherif El Kettani. "About Fully Homomorphic Encryption Improvement Techniques." International Journal of Embedded and Real-Time Communication Systems 10, no. 3 (2019): 1–20. http://dx.doi.org/10.4018/ijertcs.2019070101.

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Fully homomorphic encryption schemes (FHE) are a type of encryption algorithm dedicated to data security in cloud computing. It allows for performing computations over ciphertext. In addition to this characteristic, a verifiable FHE scheme has the capacity to allow an end user to verify the correctness of the computations done by a cloud server on his encrypted data. Since FHE schemes are known to be greedy in term of processing consumption and slow in terms of runtime execution, it is very useful to look for improvement techniques and tools to improve FHE performance. Parallelizing computatio

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Cao, Laicheng, Wenwen He, Xian Guo, and Tao Feng. "A Scheme for Verification on Data Integrity in Mobile Multicloud Computing Environment." Mathematical Problems in Engineering 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/9267608.

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In order to verify the data integrity in mobile multicloud computing environment, a MMCDIV (mobile multicloud data integrity verification) scheme is proposed. First, the computability and nondegeneracy of verification can be obtained by adopting BLS (Boneh-Lynn-Shacham) short signature scheme. Second, communication overhead is reduced based on HVR (Homomorphic Verifiable Response) with random masking and sMHT (sequence-enforced Merkle hash tree) construction. Finally, considering the resource constraints of mobile devices, data integrity is verified by lightweight computing and low data transm

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Tang, Yongli, Minglu Jin, Hui Meng, Li Yang, and Chengfu Zheng. "Attribute-Based Verifiable Conditional Proxy Re-Encryption Scheme." Entropy 25, no. 5 (2023): 822. http://dx.doi.org/10.3390/e25050822.

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There are mostly semi-honest agents in cloud computing, so agents may perform unreliable calculations during the actual execution process. In this paper, an attribute-based verifiable conditional proxy re-encryption (AB-VCPRE) scheme using a homomorphic signature is proposed to solve the problem that the current attribute-based conditional proxy re-encryption (AB-CPRE) algorithm cannot detect the illegal behavior of the agent. The scheme implements robustness, that is the re-encryption ciphertext, can be verified by the verification server, showing that the received ciphertext is correctly con

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Long, Weifeng, Jiwen Zeng, Yaying Wu, Yan Gao, and Hui Zhang. "A Certificateless Verifiable Bilinear Pair-Free Conjunctive Keyword Search Encryption Scheme for IoMT." Electronics 13, no. 8 (2024): 1449. http://dx.doi.org/10.3390/electronics13081449.

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With superior computing power and efficient data collection capability, Internet of Medical Things (IoMT) significantly improves the accuracy and convenience of medical work. As most communications are over open networks, it is critical to encrypt data to ensure confidentiality before uploading them to cloud storage servers (CSSs). Public key encryption with keyword search (PEKS) allows users to search for specific keywords in ciphertext and plays an essential role in IoMT. However, PEKS still has the following problems: 1. As a semi-trusted third party, the CSSs may provide wrong search resul

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Duan, Gangqiang, and Shuai Li. "Verifiable and Searchable Symmetric Encryption Scheme Based on the Public Key Cryptosystem." Electronics 12, no. 18 (2023): 3965. http://dx.doi.org/10.3390/electronics12183965.

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With the rapid development of Internet of Things technology and cloud computing technology, all industries need to outsource massive data to third-party clouds for storage in order to reduce storage and computing costs. Verifiable and dynamic searchable symmetric encryption is a very important cloud security technology, which supports the dynamic update of private data and allows users to perform search operations on the cloud server and verify the legitimacy of the returned results. Therefore, how to realize the dynamic search of encrypted cloud data and the effective verification of the resu

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Fan, Kai, Junxiong Wang, Xin Wang, Hui Li, and Yintang Yang. "A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing." Sensors 17, no. 7 (2017): 1695. http://dx.doi.org/10.3390/s17071695.

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Zhou, Kai, M. H. Afifi, and Jian Ren. "ExpSOS: Secure and Verifiable Outsourcing of Exponentiation Operations for Mobile Cloud Computing." IEEE Transactions on Information Forensics and Security 12, no. 11 (2017): 2518–31. http://dx.doi.org/10.1109/tifs.2017.2710941.

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Tao, Xiaoling, Kai Nie, and Yunling Wang. "Efficient publicly verifiable conjunctive keyword search over encrypted data in cloud computing." International Journal of Embedded Systems 11, no. 6 (2019): 707. http://dx.doi.org/10.1504/ijes.2019.10025616.

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Nie, Kai, Yunling Wang, and Xiaoling Tao. "Efficient publicly verifiable conjunctive keyword search over encrypted data in cloud computing." International Journal of Embedded Systems 11, no. 6 (2019): 707. http://dx.doi.org/10.1504/ijes.2019.103984.

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Mao, Jingyu. "Multi-authority attribute encryption scheme based on cloud computing verifiable outsourcing decryption." IET Conference Proceedings 2024, no. 21 (2025): 99–106. https://doi.org/10.1049/icp.2024.4209.

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Ge, Xinrui, Jia Yu, Chengyu Hu, Hanlin Zhang, and Rong Hao. "Enabling Efficient Verifiable Fuzzy Keyword Search Over Encrypted Data in Cloud Computing." IEEE Access 6 (2018): 45725–39. http://dx.doi.org/10.1109/access.2018.2866031.

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