Enterprise Security on Cloud: A Futuristic Assessment
By Enterprise Security Magazine
Security analytics is completely transforming the way companies do their business. Various changes and new trends in technologies have resulted in changing the way work is done in organizations. As a result of these drastic changes, companies have started giving more importance to their security. The cloud technology helps businesses to move faster and enables improved enterprise security.
Security analysts in government, public, and private sectors should become more sophisticated as cyber attackers increase. Businesses will distinguish the requirement of investing in tools like Security Information and Event Management (SIEM) and malware recognition systems as the fundamental resistance mechanism for cybersecurity.
SEIM came into existence in the enterprise security landscape in 2002, and it exists as a primary security analytics platform today. AlienVault (AT&T), IBM (QRadar), LogRhythm, McAfee, and Splunk are the dominant vendors who provide SIEM. Although SEIM has greatly improved over the years, the underlying architecture remains the same. SEIM has a data management layer designed for collecting and processing raw security data. After processing the data, it will be available to the upper layers of the stack for data analysis and actions like automated processes.
2018 has seen a drastic evolution and large increase in the volume of data in the architecture of SIEM. SIEM evolved with log management, with the main data source being log files. SIEM still collects, processes, and analyzes logs, but organizations now want to have the same data management services with new security telemetries, such as PCAP, NetFlow, threat intelligence, and vulnerability data. This has led to a rise in the amount of security data under management.
Creating and managing massive on-premises security analytics architecture and moving security analytics to the cloud are the two options for handling the huge amount of security data. Managing security analytics now requires a massive data management layer proficient of collecting, processing, de-duplicating, compressing, and encrypting terabytes to petabytes of data.
Cloud is here to stay; while most enterprises have already adopted cloud services, migrating security analytics infrastructure to the cloud will have to be a part of their business strategies to stay ahead of the competition curve.