www.ijecs.in International Journal Of Engineering And Computer Science Volume 10 Issue 12 December 2021, Page No. 25606-25630 ISSN: 2319-7242 DOI: 10.18535/ijecs/v10i12.4668 Venkata Bhardwaj Komaragiri, IJECS Volume 10 Issue 12 December, 2021 Page No.25586-25605 Page 25606 Enhancing Telecom Security Through Big Data Analytics and Cloud- Based Threat Intelligence Venkata Bhardwaj Komaragiri Lead Data Engineer, ORCID ID : 0009-0002-4530-3075 Abstract Negative effects of cyber-attacks against telecom operators are imposed not only on the telecom operators but also on their users. Even worse, negative effects could be imposed on national economies and on public safety. This situation happens because telecom operators are the primary communications infrastructure providers used by enterprises and people for their day-to-day operations. In the network-cloud era, telecom operators face cyber threats from both established and new attack sources. In addition, telecom operators deliver numerous services over general-purpose COTS hardware and software for lower COST, which ultimately results in larger surfaces of attack. These challenges require enhanced telecom security that can effectively improve detection, prevention, response, and recovery capabilities against advanced, massive, and patchy threats targeting telecom networks and services. Although real-time threat detection and forensic investigation can be efficiently performed using state-of-the-art techniques such as big data analytics based on statistics or machine learning models, it is challenging to understand unknown threats. This results in having to deal with an unknown threat, which is more costly than known threats. The recently proposed cloud-based threat intelligence service can fill this gap by providing threat information regarding new attack sources, tactics, methods used, signatures, and patch solutions. Such service can leverage a large telecom security consortium where a group of telecom operators share the information of their security logs and shares the cost of the threat intelligence service, which usually charges COSTs based on the size of ingested logs. The consortium must protect its ingested logs and extracted intelligence in the service from being compromised by users in the cloud. Keywords: Telecom security, big data analytics, cloud-based threat intelligence, cybersecurity, network protection, real-time threat detection, intrusion detection systems (IDS), anomaly detection, predictive analytics, data-driven security, cloud computing, scalable security solutions, advanced persistent threats (APT), threat intelligence platforms, security analytics, SIEM, telecommunications infrastructure, cyber threat mitigation, proactive security, data protection. 1. Introduction Telecommunications (telecom) service providers, such as mobile network operators, landline telephone service providers, and internet service providers, play an vital role in the critical infrastructure of a nation [1]. Telecom service providers experience cybersecurity incidents, which are either resolved or linger undetected. Cyberbad actors take advantage of previously hidden incidents, and despite strong security controls and