Related papers: When the Abyss Looks Back: Unveiling Evolving Dark…
Today, targeted online advertising relies on unique identifiers assigned to users through third-party cookies--a practice at odds with user privacy. While the web and advertising communities have proposed solutions that we refer to as…
Recommender systems that learn from implicit feedback often use large volumes of a single type of implicit user feedback, such as clicks, to enhance the prediction of sparse target behavior such as purchases. Using multiple types of…
Recently, cyber-attacks have been extensively seen due to the everlasting increase of malware in the cyber world. These attacks cause irreversible damage not only to end-users but also to corporate computer systems. Ransomware attacks such…
The rise of digital payments has accelerated the need for intelligent and scalable systems to detect fraud. This research presents an end-to-end, feature-rich machine learning framework for detecting credit card transaction anomalies and…
The increasing consumption of news online in the 21st century coincided with increased publication of disinformation, biased reporting, hate speech and other unwanted Web content. We describe BiasScanner, an application that aims to…
Enforcement of privacy regulation is essential for collaborative data analytics. In this work, we address a scenario in which two companies expect to securely join their datasets with respect to their common customers to maximize data…
Differential Privacy (DP) is being increasingly adopted for non-Euclidean data that lie on complex, high-dimensional manifolds. Existing DP mechanisms for manifold data consider geometric properties when calibrating privacy perturbations,…
Today, many web advertising data flows involve passive cross-site tracking of users. Enabling such a mechanism through the usage of third party tracking cookies (3PC) exposes sensitive user data to a large number of parties, with little…
This paper introduces the Consumer Feedback Insight & Prediction Platform, a system leveraging machine learning to analyze the extensive Consumer Financial Protection Bureau (CFPB) Complaint Database, a publicly available resource exceeding…
User devices are the largest contributor to media related global emissions. For web content, dark mode has been widely recommended as an energy-saving measure for certain display types. However, the energy savings achieved by dark mode may…
Recent advancements in computational power and algorithms have enabled unabridged data (e.g., raw images or audio) to be used as input in some models (e.g., deep learning). However, the black box nature of such models reduces their…
Current consumer-protection debates focus on the powerful new data-analysis techniques that have disrupted the balance of power between companies and their customers. Online tracking enables sellers to amass troves of historical data, apply…
Graph neural networks (GNNs) are increasingly used to model complex patterns in graph-structured data. However, enabling them to "forget" designated information remains challenging, especially under privacy regulations such as the GDPR.…
Lawmakers around the country are crafting new laws to target "dark patterns" -- user interface designs that trick or coerce users into enabling cell phone location tracking, sharing browsing data, initiating automatic billing, or making…
Over the past few years, the European Commission has made significant steps to reduce disinformation in cyberspace. One of those steps has been the introduction of the 2022 "Strengthened Code of Practice on Disinformation". Signed by…
Illicit massage businesses (IMBs) masquerade as legitimate massage parlors while facilitating commercial sex and human trafficking. Law enforcement must identify these businesses within a dense population of lawful establishments, but…
Browser fingerprinting is a growing technique for identifying and tracking users online without traditional methods like cookies. This paper gives an overview by examining the various fingerprinting techniques and analyzes the entropy and…
Online behavioral advertising (OBA) has a significant role in the digital economy. It allows advertisers to target consumers categorized according to their algorithmically inferred interests based on their behavioral data. As Alphabet and…
The advancement of AI technologies, particularly Large Language Models (LLMs), has transformed computing while introducing new security and privacy risks. Prior research shows that cybercriminals are increasingly leveraging uncensored LLMs…
Obtaining meaningful and informed consent from users is essential for ensuring autonomy and control over one's data. Notice and consent, the standard for collecting consent, has been criticized. While other individualized solutions have…