127 citations · 161 across the 25 of their papers we have counts for
26 papers
AI Potentiality and Awareness: A Position Paper from the Perspective of Human-AI Teaming in Cybersecurity
Iqbal H. Sarker, Helge Janicke, Nazeeruddin Mohammad +2
This position paper explores the broad landscape of AI potentiality in the context of cybersecurity, with a particular emphasis on its possible risk factors with awareness, which c…
Data-Driven Intelligence can Revolutionize Today's Cybersecurity World: A Position Paper
Iqbal H. Sarker, Helge Janicke, Leandros Maglaras +1
As cyber threats evolve and grow progressively more sophisticated, cyber security is becoming a more significant concern in today's digital era. Traditional security measures tend…
A Dynamic Topic Identification and Labeling Approach of COVID-19 Tweets
Khandaker Tayef Shahriar, Iqbal H. Sarker, Muhammad Nazrul Islam +1
This paper formulates the problem of dynamically identifying key topics with proper labels from COVID-19 Tweets to provide an overview of wider public opinion. Nowadays, social med…
Emotion Classification in a Resource Constrained Language Using Transformer-based Approach
Avishek Das, Omar Sharif, Mohammed Moshiul Hoque +1
Although research on emotion classification has significantly progressed in high-resource languages, it is still infancy for resource-constrained languages like Bengali. However, u…
CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks
Iqbal H. Sarker
Detecting cyber-anomalies and attacks are becoming a rising concern these days in the domain of cybersecurity. The knowledge of artificial intelligence, particularly, the machine l…
An Efficient K-means Clustering Algorithm for Analysing COVID-19
Md. Zubair, MD. Asif Iqbal, Avijeet Shil +3
COVID-19 hits the world like a storm by arising pandemic situations for most of the countries around the world. The whole world is trying to overcome this pandemic situation. A bet…
Predicting Individual Substance Abuse Vulnerability using Machine Learning Techniques
Uwaise Ibna Islam, Iqbal H. Sarker, Enamul Haque +1
Substance abuse is the unrestrained and detrimental use of psychoactive chemical substances, unauthorized drugs, and alcohol. Continuous use of these substances can ultimately lead…
An Isolation Forest Learning Based Outlier Detection Approach for Effectively Classifying Cyber Anomalies
Rony Chowdhury Ripan, Iqbal H. Sarker, Md Musfique Anwar +4
Cybersecurity has recently gained considerable interest in today's security issues because of the popularity of the Internet-of-Things (IoT), the considerable growth of mobile netw…
SentiLSTM: A Deep Learning Approach for Sentiment Analysis of Restaurant Reviews
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque +1
The amount of textual data generation has increased enormously due to the effortless access of the Internet and the evolution of various web 2.0 applications. These textual data pr…
A Survey on the Use of AI and ML for Fighting the COVID-19 Pandemic
Muhammad Nazrul Islam, Toki Tahmid Inan, Suzzana Rafi +3
Artificial intelligence (AI) and machine learning (ML) have made a paradigm shift in health care which, eventually can be used for decision support and forecasting by exploring the…
A Rule Based Expert System to Assess Coronary Artery Disease under Uncertainty
Sohrab Hossain, Dhiman Sarma, Rana Joyti Chakma +3
The coronary artery disease (CAD) involves narrowing and damaging the major blood vessels has become the most life threating disease in the world especially in south Asian reason.…
Crime Prediction Using Spatio-Temporal Data
Sohrab Hossain, Ahmed Abtahee, Imran Kashem +2
A crime is a punishable offence that is harmful for an individual and his society. It is obvious to comprehend the patterns of criminal activity to prevent them. Research can help…
BehavDT: A Behavioral Decision Tree Learning to Build User-Centric Context-Aware Predictive Model
Iqbal H. Sarker, Alan Colman, Jun Han +3
This paper formulates the problem of building a context-aware predictive model based on user diverse behavioral activities with smartphones. In the area of machine learning and dat…
CalBehav: A Machine Learning based Personalized Calendar Behavioral Model using Time-Series Smartphone Data
Iqbal H. Sarker, Alan Colman, Jun Han +2
The electronic calendar is a valuable resource nowadays for managing our daily life appointments or schedules, also known as events, ranging from professional to highly personal. R…
AppsPred: Predicting Context-Aware Smartphone Apps using Random Forest Learning
Iqbal H. Sarker, Khaled Salah
Due to the popularity of context-awareness in the Internet of Things (IoT) and the recent advanced features in the most popular IoT device, i.e., smartphone, modeling and predictin…
E-MIIM: An Ensemble Learning based Context-Aware Mobile Telephony Model for Intelligent Interruption Management
Iqbal H. Sarker, A. S. M. Kayes, Md Hasan Furhad +2
Nowadays, mobile telephony interruptions in our daily life activities are common because of the inappropriate ringing notifications of incoming phone calls in different contexts. S…
A Machine Learning based Robust Prediction Model for Real-life Mobile Phone Data
Iqbal H. Sarker
Real-life mobile phone data may contain noisy instances, which is a fundamental issue for building a prediction model with many potential negative consequences. The complexity of t…
Performance Analysis of Machine Learning Techniques to Predict Diabetes Mellitus
Md. Faisal Faruque, Asaduzzaman, Iqbal H. Sarker
Diabetes mellitus is a common disease of human body caused by a group of metabolic disorders where the sugar levels over a prolonged period is very high. It affects different organ…
Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior
Iqbal H. Sarker, Alan Colman, MA Kabir +1
Mobile phones can record individual's daily behavioral data as a time-series. In this paper, we present an effective time-series segmentation technique that extracts optimal time s…
Research Issues in Mining User Behavioral Rules for Context-Aware Intelligent Mobile Applications
Iqbal H. Sarker
Context-awareness in smart mobile applications is a growing area of study, because of it's intelligence in the applications. In order to build context-aware intelligent application…
Understanding the Role of Data-Centric Social Context in Personalized Mobile Applications
Iqbal H. Sarker
Context-awareness in personalized mobile applications is a growing area of study. Social context is one of the most important sources of information in human-activity based applica…
Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications
Iqbal H. Sarker
Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users' diverse activities with mobile phones is available around us.…
SilentPhone: Inferring User Unavailability based Opportune Moments to Minimize Call Interruptions
Iqbal H. Sarker
The increasing popularity of cell phones has made them the most personal and ubiquitous communication devices nowadays. Typically, the ringing notifications of mobile phones are us…
Mining User Behavioral Rules from Smartphone Data through Association Analysis
Iqbal H. Sarker, Flora D. Salim
The increasing popularity of smart mobile phones and their powerful sensing capabilities have enabled the collection of rich contextual information and mobile phone usage records t…