Publications (9)
Blockchain Consensus Algorithms: A Survey
Md Sadek Ferdous, Mohammad Jabed Morshed Chowdhury, Mohammad A. Hoque +1
In recent years, blockchain technology has received unparalleled attention from academia, industry, and governments all around the world. It is considered a technological breakthro…
Identifying Recent Behavioral Data Length in Mobile Phone Log
Iqbal H. Sarker, Muhammad Ashad Kabir, Alan Colman +1
Mobile phone log data (e.g., phone call log) is not static as it is progressively added to day-by-day according to individ- ual's diverse behaviors with mobile phones. Since human…
FM4SN: A Feature-Oriented Approach to Tenant-Driven Customization of Multi-Tenant Service Networks
Indika Kumara, Jun Han, Alan Colman +2
In a multi-tenant service network, multiple virtual service networks (VSNs), one for each tenant, coexist on the same service network. The tenants themselves need to be able to dyn…
A Policy Model and Framework for Context-Aware Access Control to Information Resources
A. S. M. Kayes, Jun Han, Wenny Rahayu +2
In today's dynamic ICT environments, the ability to control users' access to resources becomes ever important. On the one hand, it should adapt to the users' changing needs; on the…
SDSN@RT: a middleware environment for single-instance multi-tenant cloud applications
Indika Kumara, Jun Han, Alan Colman +3
With the Single-Instance Multi-Tenancy (SIMT) model for composite Software-as-a-Service (SaaS) applications, a single composite application instance can host multiple tenants, yiel…
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…
An Improved Naive Bayes Classifier-based Noise Detection Technique for Classifying User Phone Call Behavior
Iqbal H. Sarker, Muhammad Ashad Kabir, Alan Colman +1
The presence of noisy instances in mobile phone data is a fundamental issue for classifying user phone call behavior (i.e., accept, reject, missed and outgoing), with many potentia…
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…
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…