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Dynamic and adaptive security mechanism for Internet of Things (IoT) (Advert Reference: RDF20/EE/CIS/KHAN)

  • Full or part time
  • Application Deadline
    Friday, January 24, 2020
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

In the last two decades, the Internet of things (IoT) receives a lot of attention in academic areas and industry. The IoT changes the traditional thinking of humans by connecting many objects to the network. For instance, it connects household appliances, vehicles, wearable devices, and other electronic devices together on the network to make human life more intelligent and comfortable. The IoT network contains low power tiny devices to high power large devices such as end servers. Each device has different computation, storage, and energy consumption capabilities which makes them different among each other.

Besides the IoT infrastructure, lot of security solutions have been proposed for different security and threat models in the literature. However, the question arises that how one security solution can be dynamic in nature to adapt to the entire IoT network despite looking to the heterogeneous devices. Hence, single security solution cannot be deployed to the entire IoT infrastructure. This Ph.D. work will focus on to develop a security mechanism that applies to the existing devices and then dynamically capable enough to adapt to the newly added devices to the IoT network rather than focusing on its heterogeneity. This Ph.D. will investigate and innovate security mechanisms against different security issues of IoT by using different emerging technologies including blockchain, artificial intelligence techniques, etc to get the intelligent system in play.

The Ph.D. will be supervised by Dr. Suleman Khan, who is a faculty member and active research member in the Network Systems and Security Research Group at Computer and Information Sciences Department. The second supervisor will be Dr Nauman Aslam. Applicants should have some knowledge background in IoT, blockchain, cybersecurity and artificial intelligence. Furthermore, following skills are highly desirable for this project

IoT simulation tools (eg. Cooja/Contiki)
Computer programming (Python/Java or C++)
Mathematical Modelling
Good oral communication and writing skills

Eligibility and How to Apply:

Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF20/EE/CIS/KHAN) will not be considered.

Deadline for applications: Friday 24 January 2020

Start Date: 1 October 2020

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality.

Funding Notes

The studentship is available to Home/EU/ Worldwide students where a full stipend, paid for three years at RCUK rates (for 2019/20, this is £15,009 pa) and full fees.

References

1. Jiachen Yang, Shuai Xiao, Bin Jiang, Houbing Song, Suleman Khan, Saif ul Islam, Cache-enabled Unmanned Aerial Vehicles for Cooperative Cognitive Radio Networks, IEEE Wireless Communications, 2019

2. Mohammad Alauthman, Nauman Aslam, Mouhammd Alkasassbeh, Suleman Khan, Kim-Kwang Raymond Choo, An efficient reinforcement learning-based Botnet detection approach, Journal of Network and Computer Applications, 2019

3. Abdelmuttlib Ibrahim Abdalla Ahmed, Siti Hafizah Ab Hamid, Abdullah Gani, Suleman Khan, Muhammad Khurram Khan, Trust and reputation for Internet of Things: Fundamentals, taxonomy, and open Research Challenges, Journal of Network and Computer Applications, 2019

4. M A Manazir Ahsan, Ihsan Ali, Muhammad Imran, Mohd. Yamani Idna Idris, Suleman Khan, Anwar Khan, A Fog-centric Secure Cloud Storage Scheme, IEEE Transactions on Sustainable Computing, 2019

5. Muhammad Shiraz, Laleh Boroumand, Abdullah Gani, Suleman Khan, An Improved Port Knocking Authentication Framework for Mobile Cloud Computing, Malaysian Journal of Computer Science, 2019

6. Waleed Shahjehan, Asad Riaz, Imran Khan, Ali Safaa Sadiq, Suleman Khan, Muhammad Khurram Khan, Bat algorithm–based beamforming for mmWave massive MIMO systems, International Journal of Communication Systems, 2019

7. Safar A Maghdid, Halgurd S Maghdid, Sherko R HmaSalah, Kayhan Z Ghafoor, Ali Safaa Sadiq, Suleman Khan, Indoor human tracking mechanism using integrated onboard smartphones Wi-Fi device and inertial sensors, Telecommunication systems, 2019

8. Hina Rafique, Munam Ali Shah, Saif Ul Islam, Tahir Maqsood, Suleman Khan, Carsten Maple, A Novel Bio-Inspired Hybrid Algorithm (NBIHA) for Efficient Resource Management in Fog Computing, IEEE Access, 2019

9. Bilal Khalid Dar, Munam Ali Shah, Saif ul Islam, Carsten Maple, Shafaq Mussadiq, Suleman Khan, Delay-Aware Accident Detection and Response System using Fog Computing, IEEE Access, 2019

10. Muhammad Usman Younus, Saif ul Islam, Ihsan Ali, Suleman Khan, Muhammad Khurram Khan, A survey on software defined networking enabled smart buildings: Architecture, challenges and use cases, Journal of Network and Computer Applications, 2019

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