Can AI Solve the Lack of Manpower & Expertise in Cybersecurity?

There are several factors why organizations today lack in house AI & cybersecurity expertise:

  1. Cybersecurity and AI professionals are in high demand, but not enough supply exists.
  2. According to a research carried out in the UK cyber security labor market, on behalf of the Department for Digital, Culture, Media and Sport (DCMS), approximately 680,000 businesses (50%) have a basic skills gap in cybersecurity.
  3. The responsibility for cybersecurity handling in small-medium companies usually placed on the IT Manager who has limited time and resources to stay current with new and innovative technologies and releases.

The problem is made worse by the fact that it takes human analysts to comb through the security alerts and other “noise” to identify possible threats to the organization. This is not possible with a small IT team. Even when a company has a full complement of specialized cybersecurity teams, systems, and other resources, this still can occur.

The use of Artificial Intelligent (AI), and Machine Learning (ML), can significantly improve security by increasing the amount of data that can be analyzed – a particularly important aspect of threat detection. There is no doubt This would reduce the likelihood and impact of cyber events. AI and ML can uncover more security vulnerabilities and identify real threats faster than humans can. Despite this, due to a lack of well-trained AI/cybersecurity team members, the burden of cybersecurity threat detection often falls on unqualified and inexperienced IT staff, which subsequently increases an organization’s risk of becoming a target.

Consider the overwhelming volume of threat alerts that cybersecurity teams are exposed to each that could easily reach more than 5,000 per day. In this case, AI can feed these alerts through powerful threat models to assign severity profiles, so that busy security teams can quickly investigate them and present the higher-risk ones, rather than others that are just “noise.” This drastically helps to reduce the number of alerts that must be dealt with each day.

The use of artificial intelligence in cybersecurity tools like CYBOWALL becomes a win-win: Not only do they help find real threats, but they do it much faster than past methods. For instance, where human teams may have once required days (or even weeks) for exploration and understanding the nature of cyber threats in their network, these AI capabilities can complete the analysis in just a matter of seconds. 

An effective threat detection solution must work across the entire organization – overall physical sites, remote users, data centers, and cloud environments. If security teams need an extensive stack of tools to do this, it adds extra effort and complexity, which equals lost time and risk to properly detect, verify, and stop attacks.

CYBOWALL allows its users to automatically process no less than 8 security engines through a unified management platform that includes asset management protection, vulnerability assessment, intrusion detection, anomalies, malware hunter, honeypot, file integrity monitoring, and SIEM. These are orchestrated by a powerful AI Attack Hunter, an autonomous machine learning & multi-step g and multi-step attack hunting.

This innovative approach enables the IT security teams to monitor larger volumes of suspicious behavior while reducing the false positives, giving the teams a load of work that can handle. The fact that the results from all these security engines are collated into one easily managed dashboard means that the IT security teams don’t have to toggle from one solution to the next, saving them precious time while increasing productivity.

So to answer the question of whether AI can solve the lack of manpower and expertise in cybersecurity, the answer is a resounding yes.

To learn more and to book a demo click here.

Written by: Ziv Simhon, VP of Sales at CYBOWALL