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Dr Ryad Soobhany

About Dr Ryad Soobhany

Ryad obtained his PhD in Computer Science and Multimedia Forensics from Keele University, UK. He worked as a Digital Forensics Researcher at Forensic Pathways Ltd before joining Leeds Beckett University, UK as a Research Fellow.

Ryad's PhD research was in the area of multimedia forensics and machine learning. A method was developed to link digital images to their imaging source devices by extracting the PRNU (Photo Response Non-Uniformity) as a digital fingerprint.

The research work was continued during Ryad's time at Forensic Pathways and the Forensic Image Analyser (FIA) application was released, which is a commercial image analyser tool that allows the identification and clustering of digital photographs using the Sensor Pattern Noise (SPN). Ryad has also contributed on projects in the area of Social Network Analysis and Mobile Forensics.

Ryad has joined the CARI (Cybercrime Analysis Research and Innovation) project at Leeds Beckett University as a Research Fellow. The project is a collaboration between Leeds Beckett University and West Yorkshire Police (WYP) to investigate and improve WYP response to cybercrime and use of digital evidence.

Research Interests

Ryad has expertise in the area of Multimedia Forensics, where he helped develop and commercialise the FIA application at Forensic Pathways. The FIA was built from the research performed and published by Ryad. The FIA tool has been used in Child Sexual Abuse cases in the UK.

Ryad's current research on the CARI project involves looking into the areas of cybercrime and digital evidence. One of the main objective of the research project is to use evidence-based approach together with machine learning and statistical analysis to help the WYP. One of the outcome of CARI is to standardise and speed up the response of the police force when dealing with cybercrime.

Selected Publications

Journal articles (2)

  • Soobhany AR; Lam KP; Fletcher P; Collins DJ (2015), Mobile camera source identification with SVD. Lecture Notes in Electrical Engineering, vol. 313
  • Soobhany AR; Leary R; Lam KP (2011), On the Performance of Li's Unsupervised Image Classifier and the Optimal Cropping Position of Images for Forensic Investigations. International Journal of Digital Crime and Forensics (IJDCF), vol. 3 (1), p. 1-1.

Conference contributions (1)

  • Soobhany AR; Sheikh Akbari A; Schreuders ZC (2017) Reinforced source camera identification using non-decimated wavelet transform Wuhan, China 20170513. : .
    View Repository Record

Conference proceedings (peer reviewed) (3)

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