96 citations · 259 across the 31 of their papers we have counts for
14 papers · 1 filter
Phishing Detection through Email Embeddings
Luis Felipe Gutiérrez, Faranak Abri, Miriam Armstrong +2
The problem of detecting phishing emails through machine learning techniques has been discussed extensively in the literature. Conventional and state-of-the-art machine learning al…
A Survey on Vulnerabilities of Ethereum Smart Contracts
Zulfiqar Ali Khan, Akbar Siami Namin
Smart contract (SC) is an extension of BlockChain technology. Ethereum BlockChain was the first to incorporate SC and thus started a new era of crypto-currencies and electronic tra…
Predicting Emotions Perceived from Sounds
Faranak Abri, Luis Felipe Gutiérrez, Akbar Siami Namin +2
Sonification is the science of communication of data and events to users through sounds. Auditory icons, earcons, and speech are the common auditory display schemes utilized in son…
A Concern Analysis of FOMC Statements Comparing The Great Recession and The COVID-19 Pandemic
Luis Felipe Gutiérrez, Sima Siami-Namini, Neda Tavakoli +1
It is important and informative to compare and contrast major economic crises in order to confront novel and unknown cases such as the COVID-19 pandemic. The 2006 Great Recession a…
Cyber-Attack Consequence Prediction
Prerit Datta, Natalie Lodinger, Akbar Siami Namin +1
Cyber-physical systems posit a complex number of security challenges due to interconnection of heterogeneous devices having limited processing, communication, and power capabilitie…
Fake Reviews Detection through Analysis of Linguistic Features
Faranak Abri, Luis Felipe Gutierrez, Akbar Siami Namin +2
Online reviews play an integral part for success or failure of businesses. Prior to purchasing services or goods, customers first review the online comments submitted by previous c…
Fast Fourier Transformation for Optimizing Convolutional Neural Networks in Object Recognition
Varsha Nair, Moitrayee Chatterjee, Neda Tavakoli +2
This paper proposes to use Fast Fourier Transformation-based U-Net (a refined fully convolutional networks) and perform image convolution in neural networks. Leveraging the Fast Fo…
Vulnerability Coverage as an Adequacy Testing Criterion
Shuvalaxmi Dass, Akbar Siami Namin
Mainstream software applications and tools are the configurable platforms with an enormous number of parameters along with their values. Certain settings and possible interactions…
Detection of Coincidentally Correct Test Cases through Random Forests
Shuvalaxmi Dass, Xiaozhen Xue, Akbar Siami Namin
The performance of coverage-based fault localization greatly depends on the quality of test cases being executed. These test cases execute some lines of the given program and deter…
Vulnerability Coverage for Secure Configuration
Shuvalaxmi Dass, Akbar Siami Namin
We present a novel idea on adequacy testing called ``{vulnerability coverage}.'' The introduced coverage measure examines the underlying software for the presence of certain classe…
Cloud as an Attack Platform
Moitrayee Chatterjee, Prerit Datta, Faranak Abri +2
We present an exploratory study of responses from security professionals and ethical hackers in order to understand how they abuse cloud platforms for attack purposes. The par…
Fake Reviews Detection through Ensemble Learning
Luis Gutierrez-Espinoza, Faranak Abri, Akbar Siami Namin +2
Customers represent their satisfactions of consuming products by sharing their experiences through the utilization of online reviews. Several machine learning-based approaches can…
Launching Stealth Attacks using Cloud
Moitrayee Chatterjee, Prerit Datta, Faranak Abri +2
Cloud computing offers users scalable platforms and low resource cost. At the same time, the off-site location of the resources of this service model makes it more vulnerable to ce…
Clustering Time Series Data through Autoencoder-based Deep Learning Models
Neda Tavakoli, Sima Siami-Namini, Mahdi Adl Khanghah +2
Machine learning and in particular deep learning algorithms are the emerging approaches to data analysis. These techniques have transformed traditional data mining-based analysis r…