• Home
  • Institut FEMTO-ST
  • Département Informatique des Systèmes Complexes (DISC)
  • Sheikh Shah Mohammad Motiur Rahman
Sheikh Shah Mohammad Motiur Rahman

Sheikh Shah Mohammad Motiur Rahman
Institut FEMTO-ST | FEMTO ST · Département Informatique des Systèmes Complexes (DISC)

PhD in Electron Microscopy Image Denoising and Restoration (Ongoing)
Deep learning for the denoising and restoration of images from a scanning electron microscope for the 3D metrology

About

29
Publications
6,408
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
114
Citations
Introduction
Thirsty to learn. Curious to discover thyself. Passionate to draw new conclusions.
Additional affiliations
September 2019 - May 2022
Daffodil International University
Position
  • Senior Lecturer
Description
  • On leave
September 2017 - August 2019
Daffodil International University
Position
  • Lecturer
Education
October 2021 - September 2024
University Bourgogne Franche-Comté
Field of study
  • Microscopy Image Denoising and Restoration (Deep learning approach)
September 2020 - August 2021
University Bourgogne Franche-Comté
Field of study
  • Internet of Things
May 2017 - May 2018
Jahangirnagar University
Field of study
  • Computer Science

Publications

Publications (29)
Chapter
Social media is using rapidly for expressing user’s opinions and feelings. At present, ‘Depression’ is propagating in a cursory way which is the reason for the increasing rate of suicides even more. Recently, the status on social media can give the hints of user’s mental state along with the situation and activities that are happening with them. Di...
Chapter
Fake news is any content or information that is false and often generated to mislead its readers in believing something which is not true. Fake news has become one of major threats that can harm someone’s reputation. It often circulates wrong or made up information about various products, events, people or entity. The deliberate making of such news...
Chapter
Android Malware has grown dramatically day by day because of the rising trends of android operating based smartphones. It has become the main attraction point by attackers now-a-days. Thus, android malware detection has become a major field of investigation among the researchers and academicians who are working with in the field of cyber security....
Chapter
Alongside the recognition of the android operating system (OS), android malware is on the increase. Cybercriminals are using different techniques to develop malware for android devices. In addition, malware authors are trying to make malicious android applications that severely undermine the potential of traditional malware detectors. The key purpo...
Chapter
Phishing is an alarming issue among the cybercriminals. In the last decade, online services have revolutionized the world. Due to the revolutionary transformations of web service, the reliance on the web has increased day by day. Security threats have emerged due to the increasing reliance on online orientation. There are many types of anti-phishin...
Chapter
Among the cybercriminals, the popularity of phishing has been rapidly growing day by day. Therefore, phishing has become an alarming issue to solve in the field of cybersecurity. Many researchers have already proposed several anti- phishing approaches to detect phishing in terms of email, webpages, images, or links. This study also aimed to propose...
Chapter
This paper represents a static analysis based research of android’s feature in obfuscated android malware. Android smartphone’s security and privacy of per- sonal information remain threatened because of android based device popularity. It has become a challenging and diverse area to research in information security. Though malware researchers can...
Conference Paper
Full-text available
This paper represents a simulation-based investigation of permissions in obfuscated android malware. Android malware detection has become a challenging and emerging area to research in information security because of the rapid growth of android based smartphone users. To detect malwares in android, permissions to access the functionality of android...
Chapter
Full-text available
In the area of sentiment analysis and classification, the performance of the classification tasks can be varied based on the usage of text vectorization and feature extraction methods. This paper represents a detailed investigation and analysis of the impact on feature extraction methods to attain the highest classification accuracy of the sentimen...
Chapter
In case of sharing the datasets, central authority based storage has depended solely on extensive capacity of suppliers. Suppliers who actually act as trusted third parties to exchange and store information. This model represents various issues including information accessibility and data security. Whereas, blockchain is able to maintain transactio...
Conference Paper
Number of smartphone users of android based devices is growing rapidly. Because of the popularity of the android market malware attackers are focusing in this area for their bad intentions. Therefore, android malware detection has become a demanding and rising area to research in information security. Researchers now can effortlessly detect the and...
Article
Full-text available
N-gram techniques usually used in Natural Language Processing (NLP). Those techniques along with stacked generalization has been experimented and assessed in the field of android malware detection. Beacuse of the rapidly growing of android users, android malware has become most popular among the attackers. Android malware has become gigantic topics...
Article
Full-text available
Stacked Generalization has been assessed and evaluated in the field of Phishing URLs detection. This field has become egregious area of information security. Recently, different phishing URLs detection systems have already proposed by several researchers. But due to the lack of proper machine learning algorithm selection, the performance of those s...
Chapter
Full-text available
Sentiment Detection plays a vital role worldwide to measure the acceptance level of any products, movies or facts in the market. Text vectorization (converting text from human readable to machine readable format) and machine learning algorithms are widely used to detect the sentiment of users. This paper presents and evaluates a multi-level archite...
Conference Paper
Software Defect Prediction (SDP) identifies the defect-prone modules from software source code, which helps to serve good quality software. Mostly previous cross-project SDP models were built based on single project data, where single project was used to prepare prediction models. However, this investigation represents an empirical study of SDP whe...
Chapter
Attackers or cyber criminals are getting encouraged to develop android malware because of the rapidly growing rate of android users. To detect android malware, researchers and security specialist have been started to contribute on android malware analysis and detection related tasks using machine learning algorithms. In this paper, Stacked Generali...
Conference Paper
Full-text available
Software defect prediction is related to the testing area of software industry. Several methods have been developed for the prediction of bugs in software source codes. The objective of this study is to find the inconsistency of performance between imbalances and balance data set and to find the distinction of performance between single classifier...
Conference Paper
Sentiment Detection plays a vital role worldwide to measure the acceptance level of any products, movies or facts in the market. Text vectorization (converting text from human readable to machine readable format) and machine learning algorithms are widely used to detect the sentiment of users. This paper presents and evaluates a multi-level archite...
Article
Full-text available
Text vectorization, features extraction and machine learning algorithms play a vital role to the field of sentiment classification. Accuracy of sentiment classification varies depending on various machine learning approaches, vectorization models and features extraction methods. This paper represents multiple ways of evaluations with the necessary...
Article
Full-text available
The Open Source Software Development (OSSD) is a movement, challenges many traditional and commercial theories of software development. A group of developers, programmers, and other community members develop the Open Source Software (OSS) in a collaborative manner. Community and contributors provide great support to make the source code of the soft...
Chapter
The most widely recognized relative directions are left, right, forward and backward. This paper has presented a computational technique for tracking location by learning relative directions between two intelligent agents, where two agents communicate with each other by radio signal and one intelligent agent helps another intelligent agent to find...
Chapter
Full-text available
Android is a most popular mobile-based operating system with billions of active users, which has encouraged hackers and cyber-criminals to push the malware into this operating system. Accordingly, extensive research has been conducted on malware analysis and detection for Android in recent years; and Android has developed and implemented numerous s...

Network

Cited By

Projects

Projects (13)
Project
Propose a model that detect and identify the obfuscated malwares from AndroShow dataset.
Project
A phishing website tries to steal someones account password or other confidential information by tricking you into believing they're on a legitimate website. You could even land on a phishing site by mistyping a URL (web address). The goal is to identify pattern, detect and prevent phishing URLs using ML, EL, TL, RL and DL etc.