# Big Data and Digital Economy

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/big-data-and-digital-economy/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the intersection of big data and cloud computing technologies, with an emphasis on security, energy efficiency, machine learning, IoT, privacy protection, resource allocation, and cybersecurity in the context of mobile sensing. The papers cover a wide range of topics including data optimization, secure communication, efficient resource allocation, and privacy-preserving strategies. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t14347 |
| Works | 12 |

## Topic papers all

- [IP spoofing controlling with design science research methodology](https://scholariq.org/papers/ip-spoofing-controlling-with-design-science-research-methodology/)
- [A comprehensive bibliometric analysis of Big Data and Cyber Security: intellectual structure, trends, and global collaborations](https://scholariq.org/papers/a-comprehensive-bibliometric-analysis-of-big-data-and-cyber-security/)
- [New heuristic function in ant colony system for job scheduling in grid computing](https://scholariq.org/papers/new-heuristic-function-in-ant-colony-system-for-job-scheduling-in-grid-computing/)
- [Prediction of Covid-19 using Kalman filter algorithm](https://scholariq.org/papers/prediction-of-covid-19-using-kalman-filter-algorithm/)
- [Multi-model Bio-cryptographic Authentication in Cloud Storage Sharing for Higher Security](https://scholariq.org/papers/multi-model-bio-cryptographic-authentication-in-cloud-storage-sharing-for-higher/)
- [Public attitudes toward DeepSeek on Chinese social media: a study based on sentiment analysis and topic modeling](https://scholariq.org/papers/public-attitudes-toward-deepseek-on-chinese-social-media-a-study-based-on/)
- [Polygraph-Based Truth Detection System: Leveraging Machine Learning Model on Physiological and Behavioral Data Using Data Fusion](https://scholariq.org/papers/polygraph-based-truth-detection-system-leveraging-machine-learning-model-on/)
- [Privacy Protection in Learning Management Systems' Mobile Technology-Based Learning Analytics](https://scholariq.org/papers/privacy-protection-in-learning-management-systems-mobile-technology-based/)
- [Trust Vortex in Content Design for Social Media Platforms from the Perspective of Generative AI: An Empirical Study on Xiaohongshu’s Algorithmic Seeding Ecology](https://scholariq.org/papers/trust-vortex-in-content-design-for-social-media-platforms-from-the-perspective/)
- [Efficient Cost Evaluation and Hybrid Optimization-Based Heterogeneous Resource Allocation in Cloud–Edge-IoT Environment](https://scholariq.org/papers/efficient-cost-evaluation-and-hybrid-optimization-based-heterogeneous-resource/)
- [Computer Vision in the Era of Big Data: A Deep Learning-Based Analytical Perspective](https://scholariq.org/papers/computer-vision-in-the-era-of-big-data-a-deep-learning-based-analytical/)
- [AI and cloud computing: A synergy for scalable and secure solutions](https://scholariq.org/papers/ai-and-cloud-computing-a-synergy-for-scalable-and-secure-solutions/)

## Topic primary papers

- [Prediction of Covid-19 using Kalman filter algorithm](https://scholariq.org/papers/prediction-of-covid-19-using-kalman-filter-algorithm/)
- [Multi-model Bio-cryptographic Authentication in Cloud Storage Sharing for Higher Security](https://scholariq.org/papers/multi-model-bio-cryptographic-authentication-in-cloud-storage-sharing-for-higher/)
- [Polygraph-Based Truth Detection System: Leveraging Machine Learning Model on Physiological and Behavioral Data Using Data Fusion](https://scholariq.org/papers/polygraph-based-truth-detection-system-leveraging-machine-learning-model-on/)
- [Computer Vision in the Era of Big Data: A Deep Learning-Based Analytical Perspective](https://scholariq.org/papers/computer-vision-in-the-era-of-big-data-a-deep-learning-based-analytical/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.