Related papers: PerfWeb: How to Violate Web Privacy with Hardware …
The proliferation of web applications has essentially transformed modern browsers into small but powerful operating systems. Upon visiting a website, user devices run implicitly trusted script code, the execution of which is confined within…
Using mathematical modeling and human subjects experiments, this research explores the extent to which emerging webcams might leak recognizable textual and graphical information gleaming from eyeglass reflections captured by webcams. The…
A myriad of IoT devices such as bulbs, switches, speakers in a smart home environment allow users to easily control the physical world around them and facilitate their living styles through the sensors already embedded in these devices.…
Super-apps have emerged as comprehensive platforms integrating various mini-apps to provide diverse services. While super-apps offer convenience and enriched functionality, they can introduce new privacy risks. This paper reveals a new…
The collapse of social contexts has been amplified by digital infrastructures but surprisingly received insufficient attention from Web privacy scholars. Users are persistently identified within and across distinct Web contexts, in varying…
MLaaS (Machine Learning as a Service) has become popular in the cloud computing domain, allowing users to leverage cloud resources for running private inference of ML models on their data. However, ensuring user input privacy and secure…
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation or communication. Antivirus software and firewalls typically will not have access to encryption keys,…
Large Language Models (LLMs) are increasingly deployed on converged Cloud and High-Performance Computing (HPC) infrastructure. However, as LLMs handle confidential inputs and are fine-tuned on costly, proprietary datasets, their heightened…
The Tor network provides users with strong anonymity by routing their internet traffic through multiple relays. While Tor encrypts traffic and hides IP addresses, it remains vulnerable to traffic analysis attacks such as the website…
DNS over TLS (DoT) and DNS over HTTPS (DoH) encrypt DNS to guard user privacy by hiding DNS resolutions from passive adversaries. Yet, past attacks have shown that encrypted DNS is still sensitive to traffic analysis. As a consequence, RFC…
The prosperity of machine learning has also brought people's concerns about data privacy. Among them, inference attacks can implement privacy breaches in various MLaaS scenarios and model training/prediction phases. Specifically, inference…
Membership Inference Attacks exploit the vulnerabilities of exposing models trained on customer data to queries by an adversary. In a recently proposed implementation of an auditing tool for measuring privacy leakage from sensitive…
We present a study of how local frames (i.e., iframes loading content like "about:blank") are mishandled by a wide range of popular Web security and privacy tools. As a result, users of these tools remain vulnerable to the very attack…
Modern Web APIs allow developers to provide extensively customized experiences for website visitors, but the richness of the device information they provide also make them vulnerable to being abused to construct browser fingerprints,…
In this paper, we propose a new secure machine learning inference platform assisted by a small dedicated security processor, which will be easier to protect and deploy compared to today's TEEs integrated into high-performance processors.…
With the expansion of cloud services, serious concerns about the privacy of users' data arise due to the exposure of the unencrypted data to the server during computation. Various security primitives are under investigation to preserve…
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely…
Device fingerprinting is a widely used technique that allows a third party to identify a particular device. Applications of device fingerprinting include authentication, attacker identification, or software license binding. Device…
We present Tracking Protection in the Mozilla Firefox web browser. Tracking Protection is a new privacy technology to mitigate invasive tracking of users' online activity by blocking requests to tracking domains. We evaluate our approach…
Privacy-preserving machine learning (PPML) is an emerging topic to handle secure machine learning inference over sensitive data in untrusted environments. Fully homomorphic encryption (FHE) enables computation directly on encrypted data on…