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The demand for SOC-related services is increasing from all industries and sectors. The rate of adoption of the SOC has increased drastically across sectors like Healthcare, Pharma, manufacturing etc. The demand for enhanced maturity related to adoption of technologies, techniques etc., has been experienced more from the Banking and Financial services sectors.
The government and public sectors have also started to adopt SOC services. At the same time, businesses are rapidly migrating to AI/ML driven automated SOCs to predict attacks vigilantly, covering more attack surface, predicting zero-day anomaly-based attacks, better and faster detection/ response to their organization. The goal is to keep businesses running without any cyber impact and improve consumer experience. Businesses are extensively investing in SOC technologies that mature their strategy from reactive to proactive. SOCs are a function of data centres that are no longer used merely from a compliance point of view but play an integral role in detecting risks and responding real-time to ensure near zero business impact.
Security monitoring services in the SOCs are moving away from traditional SIEM based platforms to Big Data based monitoring platforms. The move to Big Data based monitoring systems provides enterprises with an ability to enhance their detection and analysis, apart from the ability to conduct anomaly and behavioral analytics, which will go a long way in being proactive. The emphasis on conducting proactive discovery of attack surfaces, identifying potential dead/orphan/ abandoned digital assets has evolved, to enhance proactivity around constant reduction of attack surfaces.
Automation has emerged as a critical element in the resolution and remediation of security/cyber incidents apart from increasing the ability of the security analysts to analyze the incidents. The more mature enterprises are exploring the subject of bringing in ‘Observability’ to the whole gamut of Security Incident lifecycle management, analysis, and response.
Adoption of technologies brings its own advantages and disadvantages to the enterprise. The adoption and emergence of AI, ML based technology platforms by enterprises is very welcome, given the fact that they provide the much-needed ability to analyze the day-to-day processes in the enterprise beyond static rules, signatures to a new world of analysis in addition to the learning from the analysis and comparing with the previously learnings.
This article was originally published on ETCISO.