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The Cybersecurity Skill Shortage Epidemic
The gap between the threat capability of modern-day attacks and the skilled personnel able to mitigate them, is perpetually widening. Technology is one way to close the gap.
October 7, 2019
3 Min Read
The cybersecurity industry is currently experiencing an epidemic. No, I’m not referring to the complex and sophisticated malware that is being generated in increasing numbers every day, but the availability of skilled personnel, available to prevent or remediate them.
In 2018-2019, 53 percent of organizations reported a "problematic shortage" of cybersecurity skills according to CSO Online. Cybersecurity Ventures predicts there will be 3.5 million cybersecurity job opening by 2021. A report coming out of Australia found that 88% of IT decision makers believe there is a shortage of cybersecurity 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 this development, 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 technology and cybersecurity leaders to ensure that organizations adopt technology tools that work to resolve this issue, rather than amplify it.
Organizations should also be looking to make sure that the solutions they purchase minimize the pressure on security personnel, rather than exacerbate it. The incorporation of next generation cyber technology, such as Deep Instinct, the first platform to apply deep learning to cybersecurity, reduces dependency on security experts in a few different ways:
As an automated zero-time prevention platform, it reduces the range of tasks normally carried out by a cyber security team. As a result of the solution predicting, preventing and analyzing threats autonomously, dependency on humans to monitor and remediate events is minimized.
The solution operates in a pre-execution stage, where attacks are prevented pre-emptively, rather than in a post execution stage which require a lot of remediation activity by an expert.
The deep learning prediction model also produces 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 needed to be investigated, inevitably overloading CISO’s 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. This is an important factor for solution providers; it means that they are not competing for the same talent pool as other industry players.
For more information on how to address the cybersecurity skills shortage, read the full article.
About The Author
Guy Caspi, CEO & Co-founder, Deep Instinct
A serial entrepreneur, Guy Caspi has spearheaded companies in senior positions through entire life cycles, from start up, accelerate 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.
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