The cybersecurity industry is currently experiencing a shortage of trained staff in epidemic proportions. While complex and sophisticated malware is generated in increasing numbers daily, the skilled personnel needed to prevent or remediate the ever-increasing malevolent code is simply not to be found.
In 2018-2019, 53 percent of organizations reported a “problematic shortage” of cybersecurity skills according to a published report. Another study predicts there will be 3.5 million cybersecurity job opening by 202, according to Cybersecurity Ventures. A report coming out of Australia found that 88 percent of IT decision makers believe there is a shortage of cyber security skills, within their own organization, but also nationally.
This alarming trend is seriously disadvantaging security efforts. At Deep Instinct, we’ve seen for a while now that security talent isn’t where it needs to be to help curb the cybercrime epidemic and until this is rectified, the industry continues to be outpaced by malicious actors.
To stem the trend, organizations need to adopt the mindset of malicious actors. This is not a mindset that can easily be transitioned into by occupational cyber experts or engineers. It draws on the skill set of those who have experience in cyber warfare, understand the objectives of an attacker and can identify the product architecture that’s required to undermine their efforts.
Unfortunately, the reality is that this gap between the threat capability of modern-day attacks and the skilled personnel able to mitigate them, is perpetually widening.
There are a number of fundamental shifts that need to happen in order to rectify the situation both on a national level and within organizations:
- There needs to be national level leadership on the issue. Governments need to pursue this issue to the extent of appointing a Minister for Cybersecurity, who would be responsible for establishing metrics, driving programs and reporting on national progress.
- A more thorough partnership between public and private enterprise where national governments adopt a more focused effort on working with the cybersecurity technology community.
- An integrated industry effort between cybersecurity leaders to ensure that organizations adopt technology tools that work to resolve this issue rather than amplify it.
Organizations should also be looking at cybersecurity products to make sure that the solutions they purchase minimize the pressure on security personnel, rather than exacerbate it. The incorporation of next gen cyber technology can apply deep learning to cybersecurity, reduces dependency on security experts in a few different ways. Here are some examples:
- An automated, zero-time prevention platform can reduce the range of tasks normally carried out by a cyber security team. As a result, software can predict, prevent, and analyze threats autonomously while minimizing the dependency on humans to monitor and remediate events.
- The deep learning prediction model can produce a far lower level of false positives. Standard solutions typically provide a false positive rate of 1%, which equates to thousands of alerts that each need to be investigated, inevitably overloading CISOs and wearing them down.
- Deep learning is designed to automatically identify the relevant features of a malicious file or vector without engineering from a cybersecurity expert. For solution providers, it means that they are not competing for the same talent pool as other industry players.
For more information, watch the on-demand webinar on current trends and the evolution of modern cyber threats.
A serial entrepreneur, Guy Caspi has spearheaded companies in senior positions through entire life cycles, from start up, accelerated growth and up to IPO in Nasdaq. Guy has in-depth knowledge of machine learning and deep learning assimilation in cybersecurity, which he has applied to his unique go-to-market execution experience.
