21 citations · 51 across the 12 of their papers we have counts for
12 papers
Binge, Bot, Repeat: Unpacking the Ecosystem of Video Piracy on Telegram
Sadikshya Gyawali, Jaishnoor Kaur, Taylor Graham +4
Telegram has emerged as a major platform for large-scale video piracy, where copyrighted content is rapidly distributed among users. Despite its prominence, the structural and oper…
Context-Aware Spear Phishing: Generative AI-Enabled Attacks Against Individuals via Public Social Media Data
Elham Pourabbas Vafa, Sayak Saha Roy, Shirin Nilizadeh
We demonstrate how publicly available social-media data and generative AI (GenAI) can be misused to automate and scale highly personalized, context-aware spear-phishing campaigns.…
"Explain, Don't Just Warn!" -- A Real-Time Framework for Generating Phishing Warnings with Contextual Cues
Sayak Saha Roy, Cesar Torres, Shirin Nilizadeh
Anti-phishing tools typically display generic warnings that offer users limited explanation on why a website is considered malicious, which can prevent end-users from developing th…
DarkGram: A Large-Scale Analysis of Cybercriminal Activity Channels on Telegram
Sayak Saha Roy, Elham Pourabbas Vafa, Kobra Khanmohammadi +1
We present the first large-scale analysis of 339 cybercriminal activity channels (CACs). Followed by over 23.8 million users, these channels share a wide array of malicious and une…
PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
Sayak Saha Roy, Shirin Nilizadeh
In this paper, we introduce PhishLang, the first fully client-side anti-phishing framework built on a lightweight ensemble framework that utilizes advanced language models to analy…
From Chatbots to PhishBots? -- Preventing Phishing scams created using ChatGPT, Google Bard and Claude
Sayak Saha Roy, Poojitha Thota, Krishna Vamsi Naragam +1
The advanced capabilities of Large Language Models (LLMs) have made them invaluable across various applications, from conversational agents and content creation to data analysis, r…
Exploring Gender-Based Toxic Speech on Twitter in Context of the #MeToo movement: A Mixed Methods Approach
Sayak Saha Roy, Ohad Gilbar, Christina Palantza +2
The #MeToo movement has catalyzed widespread public discourse surrounding sexual harassment and assault, empowering survivors to share their stories and holding perpetrators accoun…
Generating Phishing Attacks using ChatGPT
Sayak Saha Roy, Krishna Vamsi Naragam, Shirin Nilizadeh
The ability of ChatGPT to generate human-like responses and understand context has made it a popular tool for conversational agents, content creation, data analysis, and research a…
Unveiling the Risks of NFT Promotion Scams
Sayak Saha Roy, Dipanjan Das, Priyanka Bose +3
The rapid growth in popularity and hype surrounding digital assets such as art, video, and music in the form of non-fungible tokens (NFTs) has made them a lucrative investment oppo…
A Large-Scale Analysis of Phishing Websites Hosted on Free Web Hosting Domains
Sayak Saha Roy, Unique Karanjit, Shirin Nilizadeh
Free Website Building services (FWBs) provide individuals with a cost-effective and convenient way to create a website without requiring advanced technical knowledge or coding skil…
User Engagement and the Toxicity of Tweets
Nazanin Salehabadi, Anne Groggel, Mohit Singhal +2
Twitter is one of the most popular online micro-blogging and social networking platforms. This platform allows individuals to freely express opinions and interact with others regar…
Evaluating the effectiveness of Phishing Reports on Twitter
Sayak Saha Roy, Unique Karanjit, Shirin Nilizadeh
Phishing attacks are an increasingly potent web-based threat, with nearly 1.5 million websites created on a monthly basis. In this work, we present the first study towards identify…