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  2. University structure
  3. Computing
  4. Research
  5. Cybersecurity and edge system protection

Cybersecurity and edge system protection

The SHU Cyber research team aims to protect interconnected devices, network systems and services from any form of cyber-threats by providing innovative security and privacy solutions in this era of industrial 4.0.

The team focuses on resource constraint lightweight, connected edge devices such as Ad-Hoc systems, sensor networks and Internet of Things. The team is working on securing the following key application areas:

  • Internet of Medical Things (IoMT)
  • IoT solutions in supply chain
  • Ambient sensing systems and,
  • IoT based solutions for Smart Home and Smart Cities.

IoT devices are generally battery powered and have limited memory and computation, so most of the lightweight connected end devices are not incorporated with necessary security features to protect the devices and the data it generates. Jims Marchang and his team aim to find innovative secure solutions and techniques for these resource constraint devices to ensure data confidentiality, data integrity and data availability.

The team also focuses on providing seamless device & user authentication and authorization techniques, managing vulnerabilities, detecting and preventing intrusion including predictive and pre-emptive security challenges. They guarantee privacy and to ensure trust in users and to enable users to have a smooth, safe and confident adoption of IoT.

Data collection and usage

The SHU Cyber research team considers the data aspects of systems, making clear:

  • who is collecting data and what is being collected,
  • where the data is collected from,
  • why the data is collected and how the data is used,
  • the legal justification of data collection,
  • who can access data and how long it will be stored,
  • how the transferring of personal data or sharing data with other parties is conducted,
  • the rights of users, whether and which data will be deleted or corrected upon request, and
  • rights to withdraw consent to data collection, including the rights to complain to a data protection authority if data is misused.

Applications which adopt IoT and sensor based network solutions are extremely critical because they deal directly with the quality of life, smooth running of the systems, safety of the people and places involved and the success and smooth monitoring and control of their activities and businesses.

Internet of Medical Things solutions

Jims, as a research Co-Lead of Technological and Digital Innovations to Promote Independent Lives (of AWRC), also focuses on providing secure and trusted privacy aware IoMT solutions for health and wellbeing systems for technologies that aim to support quality of life and independent living. The team is working on ensuring secure IoT solution adoption for supply chain and control systems through the cluster research activity called iSec CyberNet (funded by SHU).

The other key focus of Jims is on providing end-to-end data integrity and building secure transparent systems using scalable Blockchain frameworks for resource constraint systems. Within the team, Timibloudi Enamamu works on providing a continuous authentication using biometric techniques. Abayomi Otebelaku focuses on designing trust-based sensor systems, IoMT data management using AI and software engineering techniques. IoT based security by design solutions is focussed by Soumya Basu.

Convolutional neural networks and recurrent neural networks

Jing Wang and Alex Shenfield work on convolutional neural networks (CNN) and recurrent neural networks (RNN) to provide intelligent machine learning based solutions during analysis and exploration of large volumes of unsupervised IoT and sensor data. Ajao Seun works on Content-Aware Location Inference and Misinformation in Online Social Networks whilst Augustine Ikpehai works on reliability in distributed and peer-to-peer communication methods and Shahrzad Zargari, explores the digital forensic aspect of the activity and the data such network system generate.

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