Big Data Analytics for Cyber Security


  • Muhammad Azhar Prabukusumo Universitas Budi Luhur


Big Data Analytics, CyberSecurity, Threat Intelligence, Attack Surface, Security Operating Center


The era of the Internet of Things with billions of connected devices has created an increasingly large surface for cyber attackers to exploit, resulting in the need for faster, up-to-date and accurate detection of such attacks. In the last few years the growth of data in volume, correctness, speed, and variation of data
is extremely fast. When large data sets or better known as Big Data are collected from or generated by different devices and sources, intelligent big data analysis techniques are required to mine, interpret and visualize the data. In terms of information system security, there is no protection that can guarantee that there will be no attacks or cyber simulation actions against a company or organization. Moreover, the laws governing the protection of personal data GDPR (General Data Protection Regulation), especially in Indonesia, have not been thoroughly discussed by regulators, so the use of automated tools is combined with a security operations center consisting of experts and collaborating with global threats. intelligence is the most up-to-date collaborative method as a precautionary measure and right now to be more proactive and also very useful for preventing cyber
attacks. The purpose of this research is to provide knowledge and understanding of the strengths and the importance of using automated tools or collaborating with security operations centers that have international standards in managing event logs of all IT devices owned within a company or organization so that information security systems, especially vulnerabilities from a tool can be detected early, especially regarding data leakage can be minimized.



How to Cite

Muhammad Azhar Prabukusumo. (2022). Big Data Analytics for Cyber Security. Proceedings of the Informatics Conference, 8(15), 28-33. Retrieved from



Artikel dalam Bahasa