Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Vulnerabilities / Threats //

Vulnerability Management

10:00 AM
Peter Barker
Peter Barker
Connect Directly
E-Mail vvv

How AI and Automation Can Help Bridge the Cybersecurity Talent Gap

Without the right tools and with not enough cybersecurity pros to fill the void, the talent gap will continue to widen.

As security threats have increased, organizations across the globe have invested more than $145 billion in the cybersecurity market to thwart breaches of consumers' personally identifiable information, company intellectual property, and partner data. While cybersecurity has become a priority across the world, companies are struggling with one key component to ensure operations are running as smoothly as possible: employees. 

There are plenty of employment opportunities within the cybersecurity field but unfortunately, there are not enough applicants to fill the void. Currently, there are 4 million unfilled cybersecurity jobs and that number has been increasing over time. However, there are ways to mitigate the talent shortage. Artificial intelligence (AI) and automation solutions can help fill the talent void and take on the task of protecting sensitive data. 

AI and automation will not replace employees, but they will empower organizations. With AI and automation delivering intelligent self-service and automating repetitive tasks, employees can focus much more on the issues that require significant attention and focus. Below are just a few ways companies can implement AI and automation to ensure there are no gaps in cybersecurity in the midst of this talent shortage: 

1. Granting access to applications for employees.
Companies spend far too much money managing access changes related to things such as new hires, employee transitions, terminations, and governing and auditing. By using AI and automation, companies dramatically reduce the need for this typically manual process, which helps to alleviate the skill-set gap issue. Additionally, automation mitigates rubber-stamping and the inevitable human error when granting privileges and access.

2. Empower users to help themselves and your enterprise.
Enabling end users with self-service tools can not only reduce help desk load but also improve the security posture of your organization. Even now, organizations spend a lot of money servicing help desk calls from users who have trouble accessing systems due to forgotten passwords or usernames. By implementing self-service automation, users can help themselves and avoid the costly calls to the help desk. Organizations can go further by crowdsourcing the process of reviewing security alerts. By asking users for their input on whether they recognize activity that has been flagged as anomalous, it reduces effort required by security analysts and also improves the quality of triage. 

3. Process and prioritize security alerts.
Some organizations receive over 1 million security alerts per day that must be triaged and processed. Security alerts cannot go ignored as they flag potential risks that could lead to a gap or vulnerability that allows a cybercriminal to breach the network. In addition to crowdsourcing the review of alerts, AI can help separate the signal from the noise and elevate the most important alerts to the top, with associated context to aid analysts in understanding the alert and determining the appropriate action. Furthermore, AI solutions catch what may be impossible for humans to identify. With AI-powered solutions, companies will receive alerts quickly that improve the overall efficiency and effectiveness of modern security. 

In 2019, we saw more than 7,000 breaches reported that exposed over 15 billion records. A global study from ESG and ISSA confirmed "that the cybersecurity skills shortage is exacerbating the number of data breaches," with the top two contributing factors to security incidents being a lack of adequate training of nontechnical employees and a lack of adequate cybersecurity staff. 

Hackers and bad actors will continue to attack organizations. Without the right tools and not enough cybersecurity pros to fill the jobs void, this problem will continue to grow. Organizations must turn to AI and automation to ensure personal data and intellectual property remain safer. 

Related Content:

 Learn from industry experts in a setting that is conducive to interaction and conversation about how to prepare for that "really  bad day" in cybersecurity. Click for more information and to register

Peter Barker is chief product officer at ForgeRock, driving the company's global product vision, design and development, and leading product management and all of engineering. Peter joined ForgeRock from Oracle, where he served as senior vice president and general manager of ... View Full Bio

Recommended Reading:

Comment  | 
Print  | 
More Insights
Newest First  |  Oldest First  |  Threaded View
User Rank: Apprentice
6/6/2020 | 4:59:51 PM
Re: I don't disagree.....but
Good post. I really apprecite your work.
Owanate Bestman
Owanate Bestman,
User Rank: Author
6/3/2020 | 4:08:17 AM
I don't disagree.....but
A large proportion of the skills shortages are not related to technical duties.  It's a Skills gap and studies have shown that the skills missing are not only technical but also communication skills in the form of assurance and education: the communicative need for non IT departments to understand the implications as well as limitations of security and what this means for the business.

COVID-19: Latest Security News & Commentary
Dark Reading Staff 9/25/2020
Hacking Yourself: Marie Moe and Pacemaker Security
Gary McGraw Ph.D., Co-founder Berryville Institute of Machine Learning,  9/21/2020
Startup Aims to Map and Track All the IT and Security Things
Kelly Jackson Higgins, Executive Editor at Dark Reading,  9/22/2020
Register for Dark Reading Newsletters
White Papers
Current Issue
Special Report: Computing's New Normal
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can ...
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one....
PUBLISHED: 2020-09-25
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and ...
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices f...
PUBLISHED: 2020-09-25
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `outpu...