The cybersecurity skills shortage has gained a lot of attention in recent years, and for good reason. Despite various education, upskilling and reskilling programs that have all attempted to close this gap, the results have been minimal. According to (ISC)2, there are currently 2.93 million unfilled cybersecurity positions globally. It’s time the industry admits the skills shortage is at crisis point.

One of the major contributors to the increasing skills gap is the speed at which the threat landscape is evolving. The number of threats being thrown at security analysts is increasing daily, as is the number of successful breaches against businesses worldwide. In 2017, IBM  estimated that organizations receive 200,000 security events each day – an impossible number for any human analyst to keep up with. Just imagine how much that figure has grown since then.

Staff Shortages, Team Burnout

So, how does this impact those on the front line?

With an impossible number of security events to analyze and the pressure of trying to stop all breaches, security teams suffer from mental fatigue as they spend countless hours monitoring vast numbers of alerts looking for that needle in a haystack. This has led to a generation of security analysts who are drained, stressed and frustrated. A research study by Enterprise Strategy Group and the Information Systems Security Association International revealed that as staffing shortages create a larger workload, security professionals spend more time fighting fires than performing more high-value and engaging work – a recipe for burnout.

However, it doesn’t have to be this way.

While education and training programs are extremely important in fostering critical IT knowledge and skills needed both today and tomorrow, the talent shortage is no longer something humans can fix. It’s time the industry realized that we can’t educate ourselves out of the skills gap crisis and instead look at feasible alternative solutions, in collaboration with machines.

It’s Time to Send in the Machines

To provide security teams with a fighting chance to proactively defend their organization, a security team’s cybersecurity strategy needs to find the right balance of human and machine by marrying analysts with automation.

By integrating automation into a company’s network, endpoint and intrusion monitoring workflow, analysts will be able to save a huge amount of time. The mundane, repetitive tasks like monitoring will be left to machines, decreasing the burdens placed on security teams and simplifying their tech stack. This will increase the effectiveness and efficiency of the entire security team, empowering analysts to thrive in their roles.

But to truly match the pace at which the threat landscape is growing, intelligent security solutions need to do more than automate tasks – they need to support decision making, too. That’s where Robotic Decision Automation (RDA) comes into play.

Unlike Robotic Process Automation (RPA)—which only automates very specific steps in a process—RDA leverages probability theory, provides advanced machine learning and uses the judgement and reasoning of a seasoned human analyst to make actionable decisions faster than ever before. RDA monitors, analyzes, decides and learns with the scale, speed and depth of consistent analysis found only in software. With RDA’s expert decision-making capabilities on board, the human members of security teams can proactively hunt threats, putting their skills and their time to good use.

What’s more, RDA simplifies the security tech stack and improves analyst job satisfaction by arming SecOps teams with the right software to work smarter, not harder.

Five Secrets for Security Success

Here are five secrets to managing a successful security program, even if you don’t have an enterprise-sized budget:

1. Prioritize your security data sources: Rather than becoming overwhelmed by the avalanche of data types, focus on alerting technologies that provide better indications of compromise than others. The two primary technologies here are Network Intrusion Detection and Prevention and Endpoint Detection and Response.
2. Know what matters in YOUR environment: High-value assets and accounts observed in alerts certainly makes the alerts worthier of analysis and can increase the likelihood of an actual attack. Similarly, vulnerability data and intelligence aids in understanding what could be an attack and what is likely not an attack.
3. Use machine automation: This technology has changed the game by eliminating the need to perform many of the manual tasks performed over the last several decades. The right automation solution increases security capacity and capability while reducing operating costs.
4. Choose applications rather than platforms: Steer away from complex platforms that require extensive configuration. Avoid software that requires consultants or project plans or that lack scalability.
5. Use metrics to show your success: Use three operational metrics to provide you with optimum visibility into your security programs’ performance and a way to track improvements: coverage, Time to Detection and Time to Resolution.

Streamlining for Greater Security

Analysts today are already facing burnout, so tedious tasks should no longer be part of their job responsibility. With the right technology in place, businesses can properly address the cybersecurity skills gap by arming analysts with the resources they need, giving them the time to focus on more satisfying and high-value tasks.