UK government offices often host sensitive conversations, and it is important to ensure that these are not under threat from accidental or nefarious eavesdropping attempts. These risks are continually assessed due to the high pace of change in technology.
In its latest challenge, HMGCC Co-Creation wants to hear from organisations developing artificial intelligence / machine learning techniques that provide advanced noise cancellation to help us understand what is now possible and to test in a government office scenario.
Organisations are being asked to apply if, over a 12-week period, they can develop and demonstrate technology to meet this challenge, HMGCC Co-Creation will provide funding for time, materials, overheads and other indirect expenses.
Government offices are often found in multi-occupancy buildings and open plan offices. All offices are designed to National Protective Security Agency specifications, to ensure a standard in physical and cyber protection. But there is more to learn.
Understanding risk in this type of working environment is an important function. If there is an opportunity for eavesdropping, either accidentally or by a nefarious party, we would like to understand how challenging it would be to cancel out the irrelevant ambient noise to focus in on the conversation of significance.
The latest challenge launched by HMGCC Co-Creation sets out to understand the threat of third parties using artificial intelligence (AI) / machine learning (ML) to cancel out randomised and unwanted noise.
Within office environments, there is a general noise from heating, ventilation, air conditioning systems (HVAC), desk fans, doors closing and background conversations. All of this constitutes random noise generation.
What is already known about how to cancel this noise out? Digital signal processing with adaptive filtering is well known. We want to know more about the threat of cutting-edge methods to increase signal to noise ratios, used to focus on specific conversations.
There has been a rapid rise in recent years of AI and ML adoption in most sectors. There has also been interest and advanced research into using deep learning and neural networks to provide real-time noise cancellation. HMGCC Co-Creation is now seeking to better understand the threat through testing advanced noise cancellation capabilities.
This challenge is open to sole innovators, industry, academic and research organisations of all types and sizes. There is no requirement for security clearances. Solution providers or direct collaboration from countries listed by the UK government under trade sanctions and/or arms embargoes, are not eligible for HMGCC Co-Creation challenges.
Please submit your applications to challenges@sa.catapult.org.uk
Applications must be no more than six pages or six slides in length. The page/slide limit excludes personnel CVs and organisational profiles.
There is no prescribed application format, however, please ensure your application includes the following:
All information you provide as part of your proposal – whether submitted directly to HMGCC or via a collaborator platform – will be handled in confidence.