54 citations · 181 across the 35 of their papers we have counts for
38 papers
When Technically Plausible Advice Is Unsafe: A Cross-Ecosystem Measurement of Online Support for Technology-Facilitated Abuse
Nowshin Tabassum, Solomon G. Dandekar, Morgan PettyJohn +5
Technology-facilitated abuse (TFA) creates an adversarial setting where sound cybersecurity advice can be unsafe: changing credentials or resetting devices may alert an abuser, des…
Verifying Intent and Harm: A Unified Defense Against LLM-Generated Threats
Poojitha Thota, Yun Lei, Santhosh Thangaraj +2
Large language models (LLMs) are increasingly deployed in interactive applications, yet they remain vulnerable to adversarial interactions that induce harmful, deceptive, or policy…
Detect, Unlearn, Restore: Defending Text Summarization Models Against Data Poisoning
Poojitha Thota, Shirin Nilizadeh
Training-time data poisoning during fine-tuning poses a significant threat to large language models (LLMs) deployed for abstractive text summarization, where small task-specific da…
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.…
Taming Data Challenges in ML-based Security Tasks Using Generative AI
Shravya Kanchi, Neal Mangaokar, Aravind Cheruvu +4
Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmic advancements. We argue that data cha…
"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…
FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods
Seyyed Mohammad Sadegh Moosavi Khorzooghi, Poojitha Thota, Mohit Singhal +3
The lack of a common platform and benchmark datasets for evaluating face obfuscation methods has been a challenge, with every method being tested using arbitrary experiments, datas…
Attacks against Abstractive Text Summarization Models through Lead Bias and Influence Functions
Poojitha Thota, Shirin Nilizadeh
Large Language Models have introduced novel opportunities for text comprehension and generation. Yet, they are vulnerable to adversarial perturbations and data poisoning attacks, p…
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…
Demonstration of an Adversarial Attack Against a Multimodal Vision Language Model for Pathology Imaging
Poojitha Thota, Jai Prakash Veerla, Partha Sai Guttikonda +3
In the context of medical artificial intelligence, this study explores the vulnerabilities of the Pathology Language-Image Pretraining (PLIP) model, a Vision Language Foundation mo…
Sadness, Anger, or Anxiety: Twitter Users' Emotional Responses to Toxicity in Public Conversations
Ana Aleksandric, Hanani Pankaj, Gabriela Mustata Wilson +1
Cyberbullying and online harassment have serious negative psychological and emotional consequences for the victims, such as decreased life satisfaction, suicidal ideation, self-har…
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…
Impact of Stricter Content Moderation on Parler's Users' Discourse
Nihal Kumarswamy, Mohit Singhal, Shirin Nilizadeh
Social media platforms employ various content moderation techniques to remove harmful, offensive, and hate speech content. The moderation level varies across platforms; even over t…
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…
Auditing Yelp's Business Ranking and Review Recommendation Through the Lens of Fairness
Mohit Singhal, Javier Pacheco, Seyyed Mohammad Sadegh Moosavi Khorzooghi +4
Auditing is critical to ensuring the fairness and reliability of decision-making systems. However, auditing a black-box system for bias can be challenging due to the lack of transp…
Analyzing the Stance of Facebook Posts on Abortion Considering State-level Health and Social Compositions
Ana Aleksandric, Henry Isaac Anderson, Anisha Dangal +2
Abortion remains one of the most controversial topics, especially after overturning Roe v. Wade ruling in the United States. Previous literature showed that the illegality of abort…
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…
StyleGAN as a Utility-Preserving Face De-identification Method
Seyyed Mohammad Sadegh Moosavi Khorzooghi, Shirin Nilizadeh
Face de-identification methods have been proposed to preserve users' privacy by obscuring their faces. These methods, however, can degrade the quality of photos, and they usually d…
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…
The Power of Social Norms: How Initial Responses to Toxicity Shape Conversations on Twitter
Ana Aleksandric, Mohit Singhal, Anne Groggel +1
Online harassment and abusive language continue to be a growing concern on social media platforms. In this study, we explore the power of group dynamics to shape the toxicity of Tw…