Related papers: Messaging with Purpose Limitation -- Privacy-Compl…
Online collaborative medical prediction platforms offer convenience and real-time feedback by leveraging massive electronic health records. However, growing concerns about privacy and low prediction quality can deter patient participation…
The proliferation of mobile applications and the subsequent sharing of personal data with service and application providers have given rise to substantial privacy concerns. Application marketplaces have introduced mechanisms to conform to…
As data privacy continues to be a crucial human-right concern as recognized by the UN, regulatory agencies have demanded developers obtain user permission before accessing user-sensitive data. Mainly through the use of privacy policies…
Cellular providers and data aggregating companies crowdsource celluar signal strength measurements from user devices to generate signal maps, which can be used to improve network performance. Recognizing that this data collection may be at…
The enforcement of sensitive policies in untrusted environments is still an open challenge for policy-based systems. On the one hand, taking any appropriate security decision requires access to these policies. On the other hand, if such…
Privacy by Design (PbD) is the most common approach followed by software developers who aim to reduce risks within their application designs, yet it remains commonplace for developers to retain little conceptual understanding of what is…
Current smartphone operating systems regulate application permissions by prompting users on an ask-on-first-use basis. Prior research has shown that this method is ineffective because it fails to account for context: the circumstances under…
In a Multi-Agent System (MAS), individual agents observe various aspects of the environment and transmit this information to a central entity responsible for aggregating the data and deducing system parameters. To improve overall…
This paper focuses on some shortcomings in current privacy and data protection regulations' ability to adequately address the ramifications of AI-driven data processing practices, in particular where data sets are combined and processed by…
Differential privacy is a popular privacy-enhancing technology that has been deployed both in industry and government agencies. Unfortunately, existing explanations of differential privacy fail to set accurate privacy expectations for data…
In today's mobile application marketplace, the ability of consumers to make informed choices regarding their privacy is extremely limited. Consumers largely rely on privacy policies and app permission mechanisms, but these do an inadequate…
Integrated sensing and communication (ISAC) technology is one of the featuring technologies of the next-generation communication systems. When sensing capability becomes ubiquitous, more information can be collected, which can facilitate…
An information-theoretic privacy mechanism design is studied, where an agent observes useful data $Y$ which is correlated with the private data $X$. The agent wants to reveal the information to a user, hence, the agent utilizes a privacy…
Concern about how to aggregate sensitive user data without compromising individual privacy is a major barrier to greater availability of data. The model of differential privacy has emerged as an accepted model to release sensitive…
Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional formulations impose a uniform privacy requirement for all users, which is often inconsistent with real-world scenarios…
Speech technology for communication, accessing information, and services has rapidly improved in quality. It is convenient and appealing because speech is the primary mode of communication for humans. Such technology, however, also presents…
In the traditional index coding problem, a server employs coding to send messages to $n$ clients within the same broadcast domain. Each client already has some messages as side information and requests a particular unknown message from the…
The integration of fairness and privacy in centralized data-driven applications is critical, especially as these systems increasingly influence sectors with significant societal impact. Current methods rarely address privacy, fairness, and…
IoT Trigger-Action Platforms (TAPs) typically offer coarse-grained permission controls. Even when fine-grained controls are available, users are likely overwhelmed by the complexity of setting privacy preferences. This paper contributes to…
In (single-server) Private Information Retrieval (PIR), a server holds a large database $DB$ of size $n$, and a client holds an index $i \in [n]$ and wishes to retrieve $DB[i]$ without revealing $i$ to the server. It is well known that…