Enhancing Threat Intelligence and Cyber Defense through Big Data Analytics: A Review Study
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| Název: | Enhancing Threat Intelligence and Cyber Defense through Big Data Analytics: A Review Study |
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| Autoři: | Journal of Global Research in Mathematical Archives(JGRMA) |
| Informace o vydavateli: | Zenodo, 2025. |
| Rok vydání: | 2025 |
| Témata: | Big Data Analytics, Cybersecurity, Anomaly Detection, Behavioural Analysis, Threat Intelligence, Event Correlation, Blockchain, Data Visualization, IoT Integration, Data Privacy |
| Popis: | In a number of industries, including cybersecurity, healthcare, banking, and power distribution, big data analysis has emerged as a game-changing technique. The proliferation of massive and heterogeneous information gathered from platforms, including social media, IoT devices, electronic conducted online, and network logs, necessitates advanced analytical techniques and robust technologies for effective processing and insight generation. This research investigates how statistical analysis of big data may be integrated into cybersecurity, emphasizing its role in anomaly detection, behavioral analysis, threat intelligence integration, and event correlation to enhance threat detection, response, and prediction. Despite its transformative potential, issues including security, confidentiality, effectiveness, and knowledge storage remain significant barriers to its adoption. In order to overcome these obstacles and progress in the sector, emerging technologies like blockchain integration, sophisticated data visualization, and IoT convergence provide encouraging answers. By leveraging these innovations, organizations can improve their ability to anticipate, mitigate, and respond to sophisticated cyber threats, ensuring robust protection for sensitive data and systems. |
| Druh dokumentu: | Article |
| DOI: | 10.5281/zenodo.15223173 |
| DOI: | 10.5281/zenodo.15223174 |
| Rights: | CC BY |
| Přístupové číslo: | edsair.doi.dedup.....267303f2c06674b3de83d0d7eb87e353 |
| Databáze: | OpenAIRE |
| Abstrakt: | In a number of industries, including cybersecurity, healthcare, banking, and power distribution, big data analysis has emerged as a game-changing technique. The proliferation of massive and heterogeneous information gathered from platforms, including social media, IoT devices, electronic conducted online, and network logs, necessitates advanced analytical techniques and robust technologies for effective processing and insight generation. This research investigates how statistical analysis of big data may be integrated into cybersecurity, emphasizing its role in anomaly detection, behavioral analysis, threat intelligence integration, and event correlation to enhance threat detection, response, and prediction. Despite its transformative potential, issues including security, confidentiality, effectiveness, and knowledge storage remain significant barriers to its adoption. In order to overcome these obstacles and progress in the sector, emerging technologies like blockchain integration, sophisticated data visualization, and IoT convergence provide encouraging answers. By leveraging these innovations, organizations can improve their ability to anticipate, mitigate, and respond to sophisticated cyber threats, ensuring robust protection for sensitive data and systems. |
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| DOI: | 10.5281/zenodo.15223173 |
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