Security leaders are pressured to manage the cybersecurity profile of the enterprise in the rapidly changing environment
In the current IT scenario, words traditionally utilized for human health and body have been increasingly used to describe IT. Viruses, security hygiene, training for cyber fitness, etc., are examples of such cross-industry phrases. Description and framing of IT concepts in terms of health can be highly helpful when creating security operation centers and strategies.
CIOs acknowledge that most businesses and enterprises have not maintained SOCs at the required health status. Cybersecurity requirements are highly stressful and have proven to be overwhelming due to increased alert volume. Organizations often lack the well-trained resources needed to keep in step with the influx.
Security leaders believe that, on average, SOCs receive well over ten thousand alerts per day. Many of these alerts are not addressed. The number may be on the lower side, but they could prove dangerous in the long run.
CISOs say that it is critical to organize alerts based on priority to promote a healthier environment in the cybersecurity industry. It will help reduce the stress levels of analysts. When they have more time due to the elimination of low-value alerts and false-positives processing, they have the option to analyze higher-value tasks and progress in their careers.
Application of ML and AI right from the detection step to the response step will help set up SOCs on the correct path towards reaching their vision, and improving the security posture.
Using AI and ML to improve the health of SOC
CIOs believe that AI/ML can help SOC to be more efficient in the triage, analysis, and response process. They believe that the technologies will help proactively spot threats and mitigate attacks before they disrupt the business.
Detecting known cybersecurity issues is easy. These are similar to a common medical ailment, the symptoms are common, and people may opt to directly get the medicine from the pharmacy rather than visit a doctor. Or if it’s unknown symptoms or seasonal symptoms, the doctor’s visit will yield a prescription for the pharmacy.
Similarly, in the IT industry, patches are synonyms for OTC medicines. When automation is combined with the solution, the organization gets the solution delivered to its premise rather than consulting the SOC each time.
AI/ML can detect known risks, identify the signatures, and update patches with minimal human intervention.
AI/ML will help security teams to diagnose and identify threats in the initial stages with minimal damage to the security profile or corporate network. This reduces the resolution time. AI/ML tools can easily be trained with inputs from the analysts’ decision-making skills and shadow to assist in alert disposition.
IT teams shift to emergency mode when security systems are off-kilter or a potential security breach. Immediate protection of IT assets is required and could involve calling various specialists in for support.
When curating the knowledge available to IT teams and CISOs, AI/ML can help to provide the incident response departments with forensic analysis insights and playbook access.
Better job satisfaction
CISOs clarify that implementing AI/ML in cybersecurity policies do not always refer to automation. Reduced stress and better job satisfaction that boost higher employee retention are also major benefits of this practice.
Leaders believe that when more time is spent with tabletop tests and breach simulations, the security team’s posture and knowledge shift from reactive to proactive.