Dr Hisham Al Assam

Senior Lecturer in Applied Computing

hisham.al-assam@buckingham.ac.uk

BEng in Software Engineering and Information Systems, PhD in Computer Science

Hisham-Al-Assam

Hisham is a senior lecturer in Computer Science. He currently teaches Introduction to Computer Systems, Web Applications Development and Information Security to UG students. He also teaches Web Technologies and Applications, and Information Security in Communications to MSc students.

Hisham’s key research interest is machine learning in security and healthcare. Security applications include deep learning for biometric recognition, dynamic signatures, privacy-aware biometric template security and multi-factor remote authentication. His research into healthcare focusses on the exciting field of automatic analysis of medical and biomedical images.

He has supervised/co-supervised a number of research students working on collaborative projects relevant to his research interests such as X-ray and microscopic image analysis for identifying the genetic bases of complex diseases, brain image analysis for better understating of Alzheimer’s disease, inter\intra cellular calcium analysis for understanding atrial fibrillation, and ultrasound image analysis for identifying signs of early miscarriage and different types of ovarian tumours.

Hisham is the Chair of the School’s Teaching and Learning Committee, and the School’s Academic Misconduct Officer. He is an elected Senate Member and a member of the ULTC and URC committees. He is also a member of the British Computer Society and its Information Security Specialist Group.

Hisham jointly won two Knowledge Transfer Partnerships (KTP) grants funded by Innovate UK & Deepnet Security LTD to build innovative biometric-based products. He was the academic supervisor of the two KTP projects between Jan 2015 to Feb 2018.

Tel: +44 (01280) 828276
Email: hisham.al-assam@buckingham.ac.uk

The SCE tool is a Matlab tool for automatic spine curvature estimation from X-ray images of a mouse model. Click here to download the tool. 

The EMV Tokenisation tool is a set of Java Applets for simulating a security improved protocol on EMV Contactless Card, and comparing it to the original protocol. Click here to download the tool.

The ContactlessSec is a tool that provides an implementation of three EMV authentication methods (SDA, DDA and CDA) in addition to simulating the sniffing and replay attacks on contactless cards. Click here to download the tool.

The BSE tool is a Matlab package for automatic Brain Size Estimation from X-ray images of a mouse model. Click here to download the tool and sample images.

The LayerSeg tool is a Matlab tool for automatic segmentation of H&E skin images. Click here to download the tool.

Selected Publications

  • T. Kuseler, I.A. Lami & H. Al-Assam, “Location-assured, multifactor authentication on smartphones via LTE communication”
  • T. Kuseler, I.A. Lami & & H Al-Assam, “BossPro: a biometrics-based obfuscation scheme for software protection”
  • H. Al-Assam, I.A. Lami & T. Kuseler, “Integrating Cancellable Biometrics with Geographical Location for Effective Unattended Authentication of Users of Mobile Devices”
  • H. Al-Assam, R. Rashid & S. Jassim, “Combining steganography and biometric cryptosystems for secure mutual authentication and key exchange”
  • H. Al-Assam, H. Du, S. Jassim et al., “Automatic segmentation and classification of gestational sac based on mean sac diameter using medical ultrasound image”, SPIE Conference on Multimedia/Image Processing, Security and Applications (Baltimore, USA, May 2014)
  • O. Al Okashi, H. Du, J. Selway, C. Lelliott, S. Maguire, D. Melvan, K. Langlands & H. Al-Assam, “Automatic Rib Segmentation and Counting From Mouse X-ray Images”, Proc. 18th Annual Conference in Medical Image Understanding and Analysis (MIUA, 2014), 143-148
  • S. Khazendar, J. Farren, H. Al-Assam, A. Sayasneh, H. Du, T. Bourne & S.A. Jassim, “Automatic Identification of Early Miscarriage Based on Multiple Features Extracted from Ultrasound Images”, Proc. 18th Annual Conference in Medical Image Understanding and Analysis (MIUA, 2014), 131-136
  • S. Khazendar, H. Al-Assam, H. Du, S. Jassim, A. Sayasneh, T. Bourne, J.Kajiser, and D. Timmerman, “Automated Classification of Static Ultrasound Images of Ovarian Tumours Based on Decision Level Fusion”, Sixth International Conference on Computer Science and Electronic Engineering Conference (CEEC 2014), 148-153
  • S. Khazendar, A. Sayasneh, H. Al-Assam, H. Du, J. Kaijser, L. Ferrara, D. Timmerman, S. Jassim & T. Bourne, “Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator”, Facts, Views and Visions in ObGyn 7.1 (March 2015), 7-15
  • H. Al-Assam, T. Kuseler, S. Jassim & S. Zeadally, “Privacy in Biometric Systems”, in S. Zeadally & M. Badra (eds), Privacy in a Digital, Networked World: Technologies, Implications and Solutions (Springer, 2015), 235-263
  • D. Ahmed Ibrahim, H. Al-Assam, H. Du, D. Al-karawi, S. Jassim et al., “Automatic segmentation and measurements of gestational sac using static B-mode ultrasound images”, Proc. SPIE 9869, Mobile Multimedia/Image Processing, Security, and Applications 2016
  • O. Al Okashi, H. Du & H. Al-Assam, “Automatic spine curvature estimation from X-ray images of a mouse model”, Journal of Computer Methods and Programs in Biomedicine 140 (March 2017), 175–184
  • T. Albaidhani, C. Hawkes, S. Jassim & H. Al-Assam, “Automatic detection of the hippocampal region associated with Alzheimer’s disease from microscopic images of mice brain”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications, 98690D (Baltimore, May 2016)
  • S. Hussein, J. Selway, S. Jassim and H. Al-Assam, “Automatic layer segmentation of H&E microscopic images of mice skin”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications, 98690C (Baltimore, May 2016)
  • S. Pal, H. Al-Assam and H. Sellahewa, “On the Discrimination Power of Dynamic Features for Online Signature”, accepted to appear in the 50th International Conference in Digital Signal Processing (DSP) (London, August 2017)
  • S. Hussein, S. Jassim & H Al-Assam, “Automatic Quantification of Epidermis Curvature in H&E Stained Microscopic Skin Image of Mice”, MIUA 2017: Medical Image Understanding and Analysis (July 2017, CCIS Series vol. 723), 935-945
  • D. Traore, K. Rietdorf, N. Al-Jawad & H. Al-Assam, “Automatic Hotspots Detection for Intracellular Calcium Analysis in Fluorescence Microscopic Videos”, MIUA 2017: Medical Image Understanding and Analysis (July 2017, CCIS Series vol. 723), 862-873
  • D. Ibrahim, H. Al-Assam, S. Jassim & H. Du, “Multi-level Trainable Segmentation for Measuring Gestational and Yolk Sacs from Ultrasound Images“, MIUA 2017: Medical Image Understanding and Analysis (July 2017, CCIS Series vol. 723), 86-97
  • D. Al-Karawi, A. Sayasneh, H. Al-Assam, S. Jassim, N. Page, D. Timmerman, T. Bourne & H. Du, “Automated differentiation of ovarian mature teratomas from other benign tumours using neural networks classification of 2D ultrasound static images”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications (May 2017), pp.102210F-102210F-10
  • D. Ibrahim, H. Al-Assam, H. Du & S. Jassim, “Trainable segmentation of multilocular cysts based on local basic pixel features”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications (May 2017), pp.102210B-102210B-8
  • O. Al-Okashi, H. Al-Assam & H. Du, “Automatic pelvis segmentation from x-ray images of a mouse model”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications (May 2017), pp.1022108-1022108-5
  • W. Hassan & H. Al-Assam, “Key Exchange Using Biometric Identity Based Encryption for Sharing Encrypted Data in Cloud Environment”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications, May 2017, pp.102210J-102210J-7
  • T. Albaidhani, S. Jassim & H. Al-Assam, “Computer aided solution for segmenting the neuron line in hippocampal microscope images”, Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications (May 2017), pp.1022109-1022109-8
  • H. Al-Assam, W.K. Hassan & S. Zeadally, “Remote Biometric Authentication for Cloud Computing”, accepted for publication in M.S. Obaidat, I. Traore & I. Woungang (eds), Biometric-based Security Systems: State of the Art and Perspectives, to be published by Cambridge University Press in Winter 2018
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