Security Technology Trends – What to Expect This Year?

AI, photo illus. by Pixabay
AI, photo illus. by Pixabay

This post is also available in: עברית (Hebrew)

The technology trends expected to affect the security sector in 2021 are shaped by how and why technologies are used, rather than heralding the emergence of completely new technologies.

Several such trends are suggested by First, trust remains at the top of the agenda. Customers and end-users are demanding transparency around how tech is used and how data is managed, especially with increased surveillance, due to the COVID-19 pandemic. This, together with the need to maintain privacy, will be a key challenge.

The next year will see momentum towards horizontal integration between environments. While recent years have seen applications and services largely designed for specific environments, the desire to achieve optimal performance, scalability, and flexibility, along with the benefits of accessing and using data at any time and from anywhere, will bring about a shift towards a more horizontal approach.

Increasingly intelligent applications and services will be deployed across all three instances – server, cloud and edge. For example, edge analytics in a surveillance camera will potentially message an operator with an alert, the operator then accessing the live video feed through a cloud-based application to verify and respond.

This shift will increase the speed and accuracy of security and surveillance – moving from reactive to proactive, manual to automated – while also reducing bandwidth, energy and cost.

AI will be employed by cybercriminals as much as in any sector, strengthening their ability to find and exploit vulnerabilities. Deep fakes will become even more sophisticated and realistic, potentially calling into doubt video surveillance evidence. As a result, further developments in methods to verify content, devices and applications in order to maintain trust in their authenticity will be required.

The move to zero trust networks will accelerate, where the security profile for each device and application is independently evaluated. 

With Machine Learning (ML) and Deep Learning (DL) now broadly available in surveillance technology, the implications of its use will be a factor in 2021. Among other applications, using these capabilities in edge devices can assist in identifying objects and reducing false positives. As a result, security experts can move to a proactive, event-based way of working, rather than continuous manual monitoring.

The COVID-19 pandemic has brought about hygiene and social distancing policies. As a result, the implementation of low- or no-contact technologies, especially in areas such as access control, will increase. In addition, surveillance solutions with people-counting capabilities will become the norm, to ensure adherence to social distancing regulations.