745
Views
0
CrossRef citations to date
0
Altmetric
Review Article

Distributed Intelligent Model for Privacy and Secrecy in Preschool Education

Article: 2222494 | Received 10 May 2023, Accepted 04 Jun 2023, Published online: 08 Jun 2023

References

  • Aggarwal, C. C. 2016. An introduction to recommender systems. vol 1. Springer International Publishing. doi:10.1007/978-3-319-29659-3_1.
  • Aira, T., K. Salin, T. Vasankari, R. Korpelainen, O. H. Jari Parkkari, K. Savonen, L. Alanko, L. Kannas, H. Selänne, and H. Selänne. 2019. Training volume and intensity of physical activity among young athletes: The health promoting sports club (HPSC) study. Advances in Physical Education 9 (4):270–2050. doi:10.4236/ape.2019.94019.
  • Alshalali, T., K. M’Bale, and D. Josyula. 2018. Security and privacy of electronic health records sharing using hyperledger fabric. Paper read at 2018 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA.
  • Alzubaidi, L., J. Zhang, A. J. Humaidi, A. Al-Dujaili, Y. Duan, O. Al-Shamma, J. Santamaría, M. A. Fadhel, M. Al-Amidie, and L. Farhan. 2021. Review of deep learning: Concepts, CNN architectures, challenges, applications, future directions. Journal of Big Data 8 (1):1–74. doi:10.1186/s40537-021-00444-8.
  • Axelsson, J., and S. Nylander. 2018. An analysis of systems-of-systems opportunities and challenges related to mobility in smart cities. Paper read at 2018 13th Annual Conference on System of Systems Engineering (SoSE), Paris, France.
  • Bellare, M., and O Goldreich. 2011. On probabilistic versus deterministic provers in the definition of proofs of knowledge. Studies in Complexity and Cryptography. Miscellanea on the Interplay Between Randomness and Computation: In Collaboration with Lidor Avigad, Mihir Bellare, Zvika Brakerski, Shafi Goldwasser, Shai Halevi, Tali Kaufman, Leonid Levin, Noam Nisan, Dana Ron, Madhu Sudan, Luca Trevisan, Salil Vadhan, Avi Wigderson, David Zuckerman 6650: 114–23.
  • Berger, J. O. 2013. Statistical decision theory and Bayesian analysis. Berlin / Heidelberg, Germany: Springer Science & Business Media.
  • Bottou, L. (2010). Large-scale machine learning with stochastic gradient descent. In Proceedings of COMPSTAT'2010: 19th International Conference on Computational StatisticsParis France, August 22-27, Large-scale machine learning with stochastic gradient descent, Proceedings of COMPSTAT'2010: 19th International Conference on Computational StatisticsParis France (pp. 177–86). Physica-Verlag HD.
  • Cai, H., Z. Liu, L. Ruiyang, and J. Chen. 2020. Leakage protection device based on smart home. Paper read at 2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS), Zhangjiajie, China.
  • Cheng, Z., T. Wang, and Y. Xin. 2018. High-order distributed consensus in multi-agent networks. Paper read at 2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS), Enshi, China.
  • Conti, M., D. Donadel, and F. Turrin. 2021. A survey on industrial control system testbeds and datasets for security research. IEEE Communications Surveys & Tutorials 23 (4):2248–94. doi:10.1109/COMST.2021.3094360.
  • Dai, J., Y. Li, H. Kaiming, and J. Sun. 2016. R-fcn: Object detection via region-based fully convolutional networks. Advances in Neural Information Processing Systems 29: 367.
  • Deka, B. K. 2016. Transformations of graph database model from multidimensional data model. Paper read at 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India.
  • Demertzis, K., L. Iliadis, and V.-D. Anezakis. 2017. Commentary: Aedes albopictus and Aedes japonicus—two invasive mosquito species with different temperature niches in Europe. Frontiers in Environmental Science 85 (5). doi:10.3389/fenvs.2017.00085.
  • Demertzis, K., L. Iliadis, and I. Bougoudis. 2020. Gryphon: A semi-supervised anomaly detection system based on one-class evolving spiking neural network. Neural Computing and Applications 32 (9):4303–14. doi:10.1007/s00521-019-04363-x.
  • Fan, C., M. Chen, X. Wang, J. Wang, and B. Huang. 2021. A review on data preprocessing techniques toward efficient and reliable knowledge discovery from building operational data. Frontiers in Energy Research 9:652801. doi:10.3389/fenrg.2021.652801.
  • Ganzfried, S. 2021. Computing Nash equilibria in multiplayer DAG-structured stochastic games with persistent imperfect information. Paper read at Decision and Game Theory for Security: 12th International Conference, GameSec 2021, Virtual Event, October 25–27, 2021, Proceedings 12, Prague, Czech Republic.
  • Goldreich, O., and O. Goldreich. 2011. Studies in complexity and cryptography. Miscellanea on the interplay between randomness and computation. vol 6650. Springer Berlin Heidelberg. doi:10.1007/978-3-642-22670-0.
  • Guo, Y., R. Zhao, S. Lai, L. Fan, X. Lei, and G. K. Karagiannidis. 2022. Distributed machine learning for multiuser mobile edge computing systems. IEEE Journal of Selected Topics in Signal Processing 16 (3):460–73. doi:10.1109/JSTSP.2022.3140660.
  • Halabi, T., M. Bellaiche, and A. Abusitta. 2018. A cooperative game for online cloud federation formation based on security risk assessment. Paper read at 2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom), Shanghai, China.
  • He, B., Y. Cui, J. Chen, and P. Xie. 2011. A spatial data mining method for mineral resources potential assessment. Paper read at Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, Fuzhou, China.
  • Hou, R., F. Tang, S. Liang, G. Ling, and Y. Zhu. 2021. Multi-party verifiable privacy-preserving federated k-means clustering in outsourced environment. Security and Communication Networks 2021 (2021):1–11. doi:10.1155/2021/3630312.
  • Ismagilova, E., L. Hughes, N. P. Rana, and Y. K. Dwivedi. 2022. Security, privacy and risks within smart cities: Literature review and development of a smart city interaction framework. Information Systems Frontiers 24 (2):393–414. doi:10.1007/s10796-020-10044-1.
  • Jain, N., A. Chaudhary, N. Sindhwani, and A. Rana. 2021. Applications of Wearable devices in IoT. Paper read at 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), Noida, India.
  • Karunarathne, S. M., N. Saxena, and M. Khurram Khan. 2021. Security and privacy in IoT smart healthcare. IEEE Internet Computing 25 (4):37–48. doi:10.1109/MIC.2021.3051675.
  • Lv, Z., W. Deng, Z. Zhang, N. Guo, and G. Yan. 2019. A data fusion and data cleaning system for smart grids big data. Paper read at 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), Xiamen, China.
  • Ma, B., S. Nie, J. Minghui, J. Song, and W. Wang. 2020. Research and analysis of sports training real-time monitoring system based on mobile artificial intelligence terminal. Wireless Communications and Mobile Computing 2020:1–10. doi:10.1155/2020/8879616.
  • Mingxiao, D., M. Xiaofeng, Z. Zhe, W. Xiangwei, and C. Qijun (2017, October). A review on consensus algorithm of blockchain. In 2017 IEEE international conference on systems, man, and cybernetics (SMC) (pp. 2567–72). IEEE.
  • Sharma, P., and J. H. Park. 2018. Blockchain based hybrid network architecture for the smart city. Future Gener Comput Systs 86:650–55. doi:10.1016/j.future.2018.04.060.
  • Shen, S., T. Zhu, D. Wu, W. Wang, and W. Zhou. 2022. From distributed machine learning to federated learning: In the view of data privacy and security. Concurrency & Computation: Practice & Experience 34 (16):e6002. doi:10.1002/cpe.6002.
  • Shivaprasad, T. K., and J. Shetty. 2017. Sentiment analysis of product reviews: A review. Paper read at 2017 International conference on inventive communication and computational technologies (ICICCT), Coimbatore.
  • Sreelakshmi, K., T. Tulasi Sasidhar, N. Mohan, and K. P. Soman. 2019. A methodology for spikes and transients detection and removal in power signals using Chebyshev approximation. Paper read at 2019 9th International Conference on Advances in Computing and Communication (ICACC), Kochi, India.
  • Weinberg, B. D., G. R. Milne, Y. G. Andonova, and F. M. Hajjat. 2015. Internet of Things: Convenience vs. privacy and secrecy. Business Horizons 58 (6):615–24. doi:10.1016/j.bushor.2015.06.005.
  • Wu, W., and A. M. Khalil. 2021. The discrete Gaussian expectation maximization (gradient) algorithm for differential privacy. Computational Intelligence and Neuroscience 2021:1–13. doi:10.1155/2021/7962489.
  • Zhou, C., A. Fu, S. Yu, W. Yang, H. Wang, and Y. Zhang. 2020. Privacy-preserving federated learning in fog computing. IEEE Internet of Things Journal 7 (11):10782–93. doi:10.1109/JIOT.2020.2987958.