Aggregated privacy-preserving auditing for cloud data integrity by Kai HE, Chuan-he HUANG, Xiao-mao WANG, Jing WANG, Jiao-li SHI

“…To solve the problem of data integrity in cloud storage,an aggregated privacy-preserving auditing scheme was proposed.To preserve data privacy against the auditor,data proof and tag proof were encrypted and combined by using the bilinearity property of the bilinear pairing on the cloud server.Furthermore,an efficient index mechanism was designed to support dynamic auditing,which could ensure that data update operations did not lead to high additional computation or communication cost.Meanwhile,an aggregation method for different proofs was designed to handle multiple auditing requests.Thus the proposed scheme could also support batch auditing for multiple owners and multiple clouds and multiple files.The communication cost of batch auditing was independent of the number of auditing requests.The theoretical analysis and experimental results show that the proposed scheme is provably secure.Compared with existing auditing scheme,the efficacy of the proposed individual auditing and batch auditing improves 21.5% and 31.8% respectively.…”
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Data update algorithm based on secure network coding in cloud environment by Hao WU, Cheng-zhe LAI, Jiu-lun FAN, Jian-hua LIU

“…In the cloud environment for data storage,the use of secure network coding technology can be a good solution to the data privacy and reliability issues.However,each coding block usually has a high correlation after network coding,very few updates to the file need to be re-encoded which is extremely easy to cause information leakage and serious consumption of system resources.To solve this problem,a network coding cloud storage data updating algorithm was proposed.Just by sending files change difference matrix,the storage node could update parts of the coding block accordingly which could complete the entire update files.Experimental results show that compared with RS coding and Tornado coding,the algorithm can not only ensure data security,but also greatly improve the efficiency of data update and data reconstruction.…”
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Research on Image Recognition and Classification Algorithms in Cloud Computing Environment Based on Deep Neural Networks by Zheshu Jia

“…Transfer learning techniques and the impact of ensemble approaches are also discussed in these articles. Data privacy, security, and the impact of AI on cloud computing are expected to become more critical in the future.…”
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Data aggregation based on the privacy-preserving element in wireless sensor networks by Wei-ni ZENG, Ya-ping LIN, Shi-ming HE, Jian-ping YU

“…A distributed mechanism was proposed to protect the data privacy during the data aggregation phase.The contributions of this mechanism are:1) Privacy-preserving element taking advantage of the algebraic properties of congruence was defined.In privacy-preserving elements,privacy data could be preserved without the extra data exchange,and the aggregation result could be recovered from the perturbed data in the cluster head.2)A flexible method for generating the privacy-preserving element was given.Thus,nodes could generate their privacy-preserving element without the extra data exchange,and the method was adapted to the dynamic reporting nodes.Extensive analysis showed that:compared with the centralized mechanism,the proposed mechanism has a better resistance to data loss,can avoid the single point problem and also consumes less communication overhead; compared with the other distributed mechanisms,the proposed mechanism is able to preserve privacy more efficiently while consuming less communication overhead.…”
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Artificial intelligence in healthcare: A focus on the best practices by Haddiya Intissar, Ramdani Sara

“…However, alongside this potential, challenges and ethical considerations remain. Data privacy, algorithmic bias, transparency of AI decision-making, and responsible use are crucial areas that require careful attention. …”
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Tracing the Blockchain Challenges in Healthcare: A Topic Modeling and Bibliometric Analysis by Mohammad Mehraeen, Laya Mahmoudi

“…As a result, five critical challenges have been identified regarding the use of blockchain in healthcare including data privacy/security, scalability, governance, interoperability and standards, and cost.…”
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A New Solution of Privacy-Preserving Public Auditing Scheme for Cloud Storage Security by Shaohui Wang, Danwei Chen, Zhiwei Wang, Suqin Chang

“…However, most of the existing auditing schemes do not consider data privacy problem. In this paper, after giving a new construction of a recently proposed primitive named aggregatable signature based broadcast encryption scheme, we present an efficient public auditing scheme with privacy property. …”
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Systematic Literature Review on Cybersecurity Issues in the Smart Home Environment by Rofiq Fauzi, Puspa Ira Dewi Candra Wulan, Danis Putra Perdana

“…Significant gaps exist in user awareness, device interoperability, data privacy, and security protocols. A multidisciplinary approach that brings together technology, policy, and social science stakeholders is recommended to build a secure, efficient, and privacy-preserving smart home ecosystem…”
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Secure deduplication and integrity audit system based on convergent encryption for cloud storage by Xiao-yong GUO, An-min FU, Bo-yu KUANG, Wei-jia DING

“…Cloud storage applications quickly become the best choice of the personal user and enterprise storage with its convenience,scalability and other advantages,secure deduplication and integrity auditing are key issues for cloud storage.At first,convergent key encapsulation/decoupling algorithm based on blind signature was set up,which could securely store key and enable it to deduplicate.Besides,a BLS signature algorithm based on convergence key was provided and use TTP to store public key and proxy audit which enables signature and pubic key deduplication and reduces client storage and computing overhead.Finally,cloud-based secure deduplicaion and integrity audit system was designed and implemented.It offered user with data privacy protection,deduplication authentication,audit authentication services and lowered client and cloud computation overhead.…”
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Risk access control model for Hadoop by Jia-shuai LI, Chang-gen PENG, Yi-jie ZHU, Hai-feng MA

“…Combining with access token and risk supervision, the risk access control mechanism for big data privacy protection was real-ized, which could be applied to enhance the security of Hadoop Kerberos protocol. …”
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Research on asynchronous robust federated learning method in vehicle computing power network by YIN Hongbo, WANG Shuai, ZHANG Ke, ZHANG Yin

“…To address the above issues, an asynchronous robust federated learning method was proposed, which achieves vehicle data privacy protection while improving the efficiency of model collaborative training through asynchronous execution of federated learning processes between vehicles. …”
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A study on Pufferfish privacy algorithm based on Gaussian mixture models by Weisan Wu

“…By leveraging a sophisticated masking mechanism, the algorithm effectively safeguards data privacy. We derive the asymptotic expressions for the Kullback–Leibler (KL) divergence and mutual information between the original and noise-added private data, thereby providing a solid theoretical foundation for the privacy guarantees of the algorithm. …”
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Research on endogenous security data sharing mechanism of F-RAN for 6G by Yang LIU, Jun LI, Wenyun CHEN, Mugen PENG

“…In order to solve the data security problem of data sharing in the fog radio access network in the 6G mobile communication system, an endogenous secure data sharing mechanism that realized local differential privacy and dynamic batch auditing was proposed.First, the user ran the RAPPOR algorithm locally on the data to protect data privacy.Next, the fog access point cached and preprocessed the data.Then the high power node performed a data integrity audit based on the BLS signature and Merkle hash tree on the data cached on the fog access point.Finally, the BBU pool infered the original distribution of shared data through statistical analysis.Security analysis and simulation show that the proposed mechanism realizes the local differential privacy of users, supports secure multi-client batch audit and data dynamic operation, and has high efficiency in time, space and communication.…”
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Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions by Santosh R. Patil, Mohmed Isaqali Karobari

“…However, challenges such as data privacy issues, algorithmic biases, and integration barriers must be addressed to enable broader adoption. …”
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Generating unseen diseases patient data using ontology enhanced generative adversarial networks by Chang Sun, Michel Dumontier

“…., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards. Generative Adversarial Networks (GANs) have been employed for this purpose, but their performance is largely constrained by their reliance on training data, rendering them inadequate for rare or previously unseen diseases. …”
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Digital Technology Adoption in the Agriculture Sector: Challenges and Complexities in Africa by David Mhlanga, Emmanuel Ndhlovu

“…These include resource scarcity, limited expertise and training, a lack of digital infrastructure, data privacy and security concerns, and resistance by farmers. …”
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Security Data Aggregation with Recoverable Data in Heterogeneous Wireless Sensor Network by Lusheng Shi, Huibo Zhu, Lin Chen

“…The algorithm uses homomorphism encryption techniques based on elliptic curve to address data privacy protection, and uses an efficient aggregate signature scheme to ensure data integrity and authenticity. …”
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The Impact of GPT Models on Education: Enhancing Learning Outcomes and Addressing Challenges by Yang Nuoya

“…It also critically examines potential issues, including data privacy concerns and the need for teachers to adapt to these new technologies. …”
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Comprehensive synthesis of mHealth interventions in psychiatry: insights from systematic, scoping, narrative reviews and content analysis by Zaakira Shahul Hameed Mahreen, Noor Azziah Zainuldin, Melvyn Weibin Zhang

“…Conclusion: Despite positive outcomes, challenges such as data privacy, user engagement and healthcare integration persist. …”
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Addressing 6 challenges in generative AI for digital health: A scoping review. by Tara Templin, Monika W Perez, Sean Sylvia, Jeff Leek, Nasa Sinnott-Armstrong

“…Generative artificial intelligence (AI) can exhibit biases, compromise data privacy, misinterpret prompts that are adversarial attacks, and produce hallucinations. …”
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