Published Paper Details:

Cloud computing has become integral to modern business operations, offering scalability, flexibility, and cost-effectiveness. However, with the increasing reliance on cloud services comes the heightened risk of security breaches and data vulnerabilities. This paper explores next-generation approaches to cloud security, focusing on the integration of big data analytics and advanced data management techniques. The utilization of big data analytics enables the proactive detection of anomalies and potential threats within cloud environments. By harnessing vast amounts of data generated by cloud systems, machine learning algorithms can identify patterns indicative of security breaches, allowing for timely intervention and mitigation strategies. Additionally, advanced data management techniques, such as encryption, tokenization, and access control mechanisms, play a crucial role in safeguarding sensitive information stored in the cloud. This paper evaluates the effectiveness of these next-gen cloud security measures in mitigating risks associated with data breaches, unauthorized access, and insider threats. Furthermore, it discusses the challenges and considerations involved in implementing these technologies, including scalability, interoperability, and regulatory compliance. In conclusion, the integration of big data analytics and advanced data management techniques represents a promising paradigm shift in cloud security, offering enhanced protection against evolving cyber threats while enabling organizations to leverage the full potential of cloud computing resources.