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20192024
most citedFake Reviews Detection through Ensemble Learning

20 citations · 54 across the 12 of their papers we have counts for

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Showing cs.CRShow all

5 papers · 1 filter

cs.CR2024

The Performance of Sequential Deep Learning Models in Detecting Phishing Websites Using Contextual Features of URLs

Saroj Gopali, Akbar S. Namin, Faranak Abri +1

Cyber attacks continue to pose significant threats to individuals and organizations, stealing sensitive data such as personally identifiable information, financial information, and…

cs.CR2020★ 4 cited

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…

cs.CR2020

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…

cs.CR2020

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…

cs.CR2019★ 9 cited

The Performance of Machine and Deep Learning Classifiers in Detecting Zero-Day Vulnerabilities

Faranak Abri, Sima Siami-Namini, Mahdi Adl Khanghah +2

The detection of zero-day attacks and vulnerabilities is a challenging problem. It is of utmost importance for network administrators to identify them with high accuracy. The highe…