In regard to rising trends and forms of attacks, a growing number of organizations opt for SIEM solutions so that they can provide a proactive measure for threat management and also acquire a detailed and centralized view of the overall security measures of their organization. Since SIEM is the foundation of a security infrastructure, there are large varieties of SIEM use cases.
Due to the revolution of the internet, cyber-attacks on unsecured networks are increasing tremendously and organizations are on the verge of data breaches. Securing proprietary information, Personally Identifiable Information (PII), or any other sensitive data have become a daunting task. Preventing business disruption, information theft, and reputational loss is necessary to thrive and survive in the competitive industry.
An industry that is worth more than $2 billion, SIEM keeps growing and evolving. The first instances of SIEMs appeared as descendants of numerous security technologies: LSM, SIM, SLM/SEM, SEC and such. The earliest versions were so limited that they were barely able to scale across large companies and were rather slow. They also needed huge teams to manage thus raising the costs ever-higher.
Vulnerability management is one of the core responsibilities of a security team. It covers assessing, reporting and if needed, mitigating on an organization’s security vulnerabilities. Yet vulnerabilities can be tackled with if and if only they are known to the IT security team. In order to find out vulnerabilities of a system or software, vulnerability scanning is conducted. It is a security technique whose purpose is identifying security weaknesses in a system. It can be conducted by individuals or network administrators for security reasons but also by hackers in order to identify the best way to gain access to a network or system.
Security analytics is not a particular tool, rather it is an approach to cybersecurity. Thorough analysis of data in order to implement proactive security measures is the essence of security analytics. It includes gathering data from every possible source to identify patterns. Nobody can predict the future but with cybersecurity analytics, you can make pretty accurate, informed guesses about it.