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Development of smart android middleware for reducing monetization through cyberattacks

The rapid growth of Internet of Things over the last few years and the working from home culture over the last 12 months as a result of Covid-19 have both contributed to the booming of the cybereconomy. People, however, have become too dependent on cyber information with often disastrous consequences as on the cyberspace neither the information is necessarily genuine nor is the source reliable.

The banking sector has been leading the field with reporting the exponential growth in all forms of digital crime across the entire world that ranges from hacking, identity theft, malware, monetary extortion, spamming just to name a few.

And despite the best advice and protection available, people keep falling victim to cybercriminals as their habits shift to 24/7 online banking, shopping, services and IoT apps.

The proliferation of the dark web is also helping cybercrime and the underground economy flourish as a new form of industry. Targets include cars, smart phones, personal computers and any IoT device that is connected and markets range from mass markets like general shopping and banking to niche markets such as healthcare, public sector services and education.

As with the software industry, the malware industry uses programs that can circumvent new detection techniques and will use social engineering through phishing, pharming, pop-ups or fake websites for financial gain In order to avoid tracking the cybercriminals use cryptocurrencies such as Bitcoin, Litecoin, Ethereum or Zcash which in turn is helping the underground economy thrive.

The primary motivation behind this research is to address monetization that results from cyberattacks by developing a smart middleware app that will minimize the risks from a cyberattack such as phishing and pharming and in turn will also learn from the process through the application of machine learning. The secondary motivation is to develop a framework of best practice in minimizing the risks and impact from cyberattacks. The project is suitable for Computer Science or Computer Engineering graduates with a research Interest in IoT. 

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)


Marios Angelides - Marios C. Angelides is a Computer Scientist, Chartered Engineer (CEng) and a Chartered Fellow of the British Computer Society (FBCS CITP). He holds a BSc (First Class Honours) and a PhD both in Computing and both from the London School of Economics (LSE) where he also began his academic career more than three decades ago specializing in Artificial Intelligence (AI). A symbolic programming language he developed as a degree finalist for coding AI applications was commercialized and then turned into his first book. He continued working on AI throughout his career and for the last two decades, he has been researching the application of creative computing techniques, such as machine learning, serious gaming, and cognitive modelling, recently in developing smart IoT apps. During this period, he published several books, including “Multimedia Information Systems” (Kluwer), “MPEG Applications” (Wiley), and “Digital Games” (IEEE/Wiley). In 2016, several years prior to joining The Computer Journal (Oxford University Press) editorial board, a paper of his that was published in The Computer Journal with a focus on “machine learning in multimedia” was the runner up winner of the annual Oxford University Press “2016 Wilkes Award”. In 2019 he was elected to the Editorial Board of The Computer Journal for which he is now serving as a Deputy Editor.

Related Research Group(s)

Creative Computing

Creative Computing - Multidisciplinary research at the intersection of Artificial Intelligence (machine learning), serious and fun gaming, and cognitive modelling to simulate a physical world either as a virtual, augmented or mixed reality environment.