4 citations · 12 across the 6 of their papers we have counts for
6 papers
ExplainableDetector: Exploring Transformer-based Language Modeling Approach for SMS Spam Detection with Explainability Analysis
Mohammad Amaz Uddin, Muhammad Nazrul Islam, Leandros Maglaras +2
SMS, or short messaging service, is a widely used and cost-effective communication medium that has sadly turned into a haven for unwanted messages, commonly known as SMS spam. With…
A Data-Driven Predictive Analysis on Cyber Security Threats with Key Risk Factors
Fatama Tuz Johora, Md Shahedul Islam Khan, Esrath Kanon +3
Cyber risk refers to the risk of defacing reputation, monetary losses, or disruption of an organization or individuals, and this situation usually occurs by the unconscious use of…
An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
Mohammad Amaz Uddin, Md Mahiuddin, Iqbal H. Sarker
Phishing email is a serious cyber threat that tries to deceive users by sending false emails with the intention of stealing confidential information or causing financial harm. Atta…
Detecting Anomalies in Blockchain Transactions using Machine Learning Classifiers and Explainability Analysis
Mohammad Hasan, Mohammad Shahriar Rahman, Helge Janicke +1
As the use of Blockchain for digital payments continues to rise in popularity, it also becomes susceptible to various malicious attacks. Successfully detecting anomalies within Blo…
Agricultural Recommendation System based on Deep Learning: A Multivariate Weather Forecasting Approach
Md Zubair, Md. Shahidul Salim, Mehrab Mustafy Rahman +3
Agriculture plays a fundamental role in driving economic growth and ensuring food security for populations around the world. Although labor-intensive agriculture has led to steady…
Exploring a Hybrid Deep Learning Framework to Automatically Discover Topic and Sentiment in COVID-19 Tweets
Khandaker Tayef Shahriar, Iqbal H. Sarker
COVID-19 has created a major public health problem worldwide and other problems such as economic crisis, unemployment, mental distress, etc. The pandemic is deadly in the world and…