Human-in-the-Loop Approach in Lawful Interception

We aim to further the capability of the technologies related to Lawful Intercept (LI) to match the needs of a rapidly changing and developing world. We aim to build on the current state of the art technology, which will be provided through our partner, and investigate ways that this can be improved to match the increasing demands of the digital world to ensure threats are detected without detriment to others. We will be working with our project partners SS8 to advance the current state-of-the-art techniques provided by their hardware in a virtualised environment to combine high speed probes with so-called smart probe technology. In this endeavour, we will also leverage our relationships with Palo Alto Networks, and IXIA solutions to create a robust and realistic test environment, capable of simulating traffic experienced in a real-world network situation. As a result of this project, we hope to have greatly increased our understanding of the field, and the overall capacity of the field to adapt to new changes in technology and usage patterns. Through our ties to industry and government it is another goal to use what we discover in this project to inform and produce valuable guidelines that will help this field continue to adapt and further provide these to the standards committees as well as UK based institutions. Our plan for this research is to be able to take the research concepts into the "real world" developing solutions to security problems as they become apparent. This will not only provide valuable innovation for the security sector but will also allow for development of the fellow and his team, and the company moving into a field that would not be possible without the support of the UKRI.
The PhD.
Year one - background research and problem understanding to which there are three key areas: human interaction with the system, state-of-the-art machine learning approaches to
this problem and familiarisation with the specific technology used by the stakeholder. Researching the challenging context and understanding the humans involved.
There is human involvement at different levels of decision making. We have to first understand who the relevant people are and how they are contributing to this pipeline. What is their level of expertise? How much time and capacity do they have to interpret - or interact with the system? What types of interpretation or explanation through interaction are suitable? For
example: inclusion of humans in the loop by providing insight and decisions to improve the algorithm's learning, this approach is less time critical and can be moved off-line. In contrast
in-line interaction and interpretation is more difficult due to the very high volumes of data being processed and might focus more on directing computation time or discarding data e.g.
filtering IoT traffic, focussing on certain IP addresses or types of communication all based on current intelligence. This research will lead to formalisations of approaches and designs
where the human is appropriately embedded in decision-making systems.
Year two
Prototyping system designs that are fast and can provide accurate insights to users through interaction. In the first instance, the student will train an offline model and compare various techniques to identify the best option form two key it is fast in producing predictions, and can be implemented in custom hardware that can work on ITSUS systems. Furthermore, this prototyping phase will serve to improve the social-technical decision making - e.g. adversary detection - through human in the loop active learning and understanding through insight interaction Supporting active learning on this massive dataset, we will need to be able to work with operators to find appropriate labels for data and verifying predictions. We will deploy an active learning framework to identify the most informative data point and get feedback on its nature from the operators.
Year 3
Refining evaluations and writing

The Centre will nurture 55 new PhD researchers who will be highly sought after in technology companies and application sectors where data and intelligence based systems are being developed and deployed. We expect that our graduates will be nationally in demand for two reasons: firstly, their training occurs in a vibrant and unique environment exposing them to challenging domains and contexts (that provide stretch, ambition and adventure to their projects and capabilities); and, secondly, because of the particular emphasis the Centre will put on people-first approaches. As one of the Google AI leads, Fei-Fei Li, recently put it, "We also want to make technology that makes humans' lives better, our world safer, our lives more productive and better. All this requires a layer of human-level communication and collaboration" [1]. We also expect substantial and attractive opportunities for the CDT's graduates to establish their careers in the Internet Coast region (Swansea Bay City Deal) and Wales. This demand will dovetail well with the lifetime of the Centre and provide momentum for its continuation after the initial EPSRC investment.

With the skills being honed in the Centre, the UK will gain a important competitive advantage which will be a strong talent based-pull, drawing in industrial investment to the UK as the recognition of and demand for human-centred interactions and collaborations with data and intelligence multiplies. Further, those graduates who wish to develop their careers in the academy will be a distinct and needed complement to the likely increased UK community of researchers in AI and big data, bringing both an ability to lead insights and innovation in core computer science (e.g., in HCI or formal methods) allied to talents to shape and challenge their research agenda through a lens that is human-centred and that involves cross-disciplinarity and co-creation.

The PhD training will be the responsibility of a team which includes research leaders in the application of big data and AI in important UK growth sectors - from health and well being to smart manufacturing - that will help the nation achieve a positive and productive economy. Our graduates will tackle impactful challenges during their training and be ready to contribute to nationally important areas from the moment they begin the next steps of their careers. Impact will be further embedded in the training programme with cohorts involved in projects that directly involve communities and stakeholders within our rich innovation ecology in Swansea and the Bay region who will co-create research and participate in deployments, trials and evaluations.

The Centre will also impact by providing evidence of and methods for integrating human-centred approaches within areas of computational science and engineering that have yet to fully exploit their value: for example, while process modelling and verification might seem much removed from the human interface, we will adapt and apply methods from human-computer interaction, one of our Centre's strengths, to develop research questions, prototyping apparatus and evaluations for such specialisms. These valuable new methodologies, embodied in our graduates, will impact on the processes adopted by a wide range of organisations we engage with and who our graduates join.

Finally, as our work is fully focused on putting the human first in big data and intelligent systems contexts, we expect to make a positive contribution to society's understandings of and involvement with these keystone technologies. We hope to reassure, encourage and empower our fellow citizens, and those globally, that in a world of "smart" technology, the most important ingredient is the human experience in all its smartness, glory, despair, joy and even mundanity.

[1] https://www.technologyreview.com/s/609060/put-humans-at-the-center-of-ai/