Dr Hannan Azhar


NameDr Hannan Azhar
Job titleSenior Lecturer
Research instituteSchool Of Engineering, Technology And Design

Research outputs

Forensic investigations of popular ephemeral messaging applications on Android and iOS platforms

Azhar, H., Cox, R. and Chamberlain, A. 2020. Forensic investigations of popular ephemeral messaging applications on Android and iOS platforms. International Journal on Advances in Security. 13 (1 & 2), pp. 41 - 53.

BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients

Casey, A., Azhar, H., Grzes, M. and Sakel, M. 2019. BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients. Disability and Rehabilitation: Assistive Technology. https://doi.org/10.1080/17483107.2019.1683239

Comparisons of forensic tools to recover ephemeral data from iOS apps used for cyberbullying

Chamberlain, A. and Azhar, H. 2019. Comparisons of forensic tools to recover ephemeral data from iOS apps used for cyberbullying. in: CYBER 2019, The Fourth International Conference on Cyber-Technologies and Cyber-Systems IARIA. pp. 88-93

Recovery of forensic artefacts from a smart home IoT ecosystem

Azhar, H. and Bate, S. 2019. Recovery of forensic artefacts from a smart home IoT ecosystem. in: CYBER 2019, The Fourth International Conference on Cyber-Technologies and Cyber-Systems IARIA. pp. 94-99

Effects of students’ preferences in use of lighting and temperature on productivity in a university setting

Azhar, H., Islam, T. and Alfieri, M. 2019. Effects of students’ preferences in use of lighting and temperature on productivity in a university setting. in: Zheng, P., Callaghan, V., Crawford, D., Kymalainen, T. and Reyes-Munoz, A. (ed.) EAI International Conference on Technology, Innovation, Entrepreneurship and Education Springer.

Use of wearable technology to measure emotional responses amongst tennis players

Azhar, H., Nelson, T. and Casey, A. 2019. Use of wearable technology to measure emotional responses amongst tennis players. in: Zheng, P., Callaghan, V., Crawford, D., Kymalainen, T. and Reyes-Munoz, A. (ed.) EAI International Conference on Technology, Innovation, Entrepreneurship and Education Springer.

A cost-effective BCI assisted technology framework for neurorehabilitation

Azhar, H., Casey, A. and Sakel, M. 2018. A cost-effective BCI assisted technology framework for neurorehabilitation.

Drone forensic analysis using open source tools

Azhar, H., Barton, T. and Islam, T. 2018. Drone forensic analysis using open source tools. Journal of Digital Forensics, Security and Law. 13 (1), pp. 7-30.

Open source forensics for a multi-platform drone system

Barton, T. and Azhar, H. 2018. Open source forensics for a multi-platform drone system. in: Matousek, P. and Schmiedecker, M. (ed.) 9th EAI International Conference on Digital Forensics & Cyber Crime Springer. pp. 83-96

Forensic analysis of popular UAV systems

Barton, T. and Azhar, H. 2017. Forensic analysis of popular UAV systems. Emerging Security Technologies (EST), 2017 Seventh International Conference on. https://doi.org/10.1109/EST.2017.8090405

An investigation on forensic opportunities to recover evidential data from mobile phones and personal computers

Naughton, P. and Azhar, H. 2017. An investigation on forensic opportunities to recover evidential data from mobile phones and personal computers.

BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients

Azhar, H., Barton, T., Casey, A. and Sakel, M. 2017. BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients. Research and Knowledge Exchange Conference 2017.

Evaluation of the MPS Predictive Policing Trial (redacted)

Bryant, R., Azhar, H., Blackburn, B. and Falade, M. 2015. Evaluation of the MPS Predictive Policing Trial (redacted).

Forensic analysis of secure ephemeral messaging applications on Android platforms

Azhar, H. and Barton, T. 2017. Forensic analysis of secure ephemeral messaging applications on Android platforms. in: Global Security, Safety and Sustainability - The Security Challenges of the Connected World: 11th International Conference, ICGS3 2017, London, UK, January 18-20, 2017, Proceedings Springer.

A wearable brain-computer interface controlled robot

Azhar, H., Badicioiu, A. and Barton, T. 2016. A wearable brain-computer interface controlled robot.

Forensic analysis of the recovery of Wickr’s ephemeral data on Android platforms

Barton, T. and Azhar, H. 2016. Forensic analysis of the recovery of Wickr’s ephemeral data on Android platforms. in: Klemas, T. and Falk, R. (ed.) CYBER 2016 : The First International Conference on Cyber-Technologies and Cyber-Systems IARIA. pp. 35-40

Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients

Deravi, F., Ang, C., Azhar, H., Al-Wabil, A., Philips, M. and Sakel, M. 2015. Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients. International Journal of Engineering and Technology Innovation (IJETI). 5 (3), pp. 165-177.

Forensic acquisitions of WhatsApp data on popular mobile platforms

Shortall, A. and Azhar, H. 2015. Forensic acquisitions of WhatsApp data on popular mobile platforms. in: Proceedings of the Sixth International Conference on Emerging Security Technologies IEEE. pp. 13-17

Automatic identification of wildlife using local binary patterns

Azhar, H., Hoque, S. and Deravi, F. 2012. Automatic identification of wildlife using local binary patterns. in: IET Conference on Image Processing (IPR 2012) Institute of Engineering and Technology. pp. 5-11

Zoometrics - biometric identification of wildlife using natural body marks

Hoque, S., Azhar, H. and Deravi, F. 2011. Zoometrics - biometric identification of wildlife using natural body marks. International Journal of Bio-Science and Bio-Technology. 3 (3), pp. 45-53.

Criticality dispersion in swarms to optimize n-tuples

Azhar, H., Deravi, F. and Dimond, K. 2008. Criticality dispersion in swarms to optimize n-tuples. in: GECCO '08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation New York Association for Computing Machinery. pp. 1-8

Particle swarm intelligence to optimize the learning of n-tuples

Azhar, H., Deravi, F. and Dimond, K. 2008. Particle swarm intelligence to optimize the learning of n-tuples. Journal of Intelligent Systems. 17 (S), pp. 169-196. https://doi.org/10.1515/JISYS.2008.17.S1.169
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