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Muhammad Khurram Khan

Researcher at King Saud University

Publications -  479
Citations -  19179

Muhammad Khurram Khan is an academic researcher from King Saud University. The author has contributed to research in topics: Authentication & Password. The author has an hindex of 64, co-authored 438 publications receiving 14170 citations. Previous affiliations of Muhammad Khurram Khan include Bahria University & Beihang University.

Papers
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Journal ArticleDOI

Medical Image Analysis using Convolutional Neural Networks: A Review

TL;DR: A comprehensive review of the current state-of-the-art in medical image analysis using deep convolutional networks is presented in this paper, where the challenges and potential of these techniques are also highlighted.
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A survey on privacy protection in blockchain system

TL;DR: The privacy threats in blockchain are analyzed and existing cryptographic defense mechanisms, i.e., anonymity and transaction privacy preservation, are discussed to preserve privacy when blockchain is used.
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Cryptanalysis and Security Improvements of ‘Two-Factor User Authentication in Wireless Sensor Networks’

TL;DR: It is shown that the M.L. Das-scheme has some critical security pitfalls and cannot be recommended for real applications, and improvements and security patches are proposed that attempt to fix the susceptibilities of his scheme.
Proceedings ArticleDOI

Diagnosing COVID-19 pneumonia from X-ray and CT images using deep learning and transfer learning algorithms

TL;DR: A simple convolution neural network and modified pre-trained AlexNet model are applied on the prepared X-rays and CT scan images and the result shows that the utilized models can provide accuracy up to 98% via pre- trained network and 94.1% accuracy by using the modified CNN.
Journal ArticleDOI

An enhanced smart card based remote user password authentication scheme

TL;DR: A modified smart card based remote user password authentication scheme to overcome the weaknesses of Chen et al.'s scheme and shows that it is user friendly and more secure than other related schemes.