Related papers: Personal Information Databases
Personal informatics (PI) systems, powered by smartphones and wearables, enable people to lead healthier lifestyles by providing meaningful and actionable insights that break down barriers between users and their health information. Today,…
Private Information Retrieval (PIR) is a fundamental cryptographic primitive that enables users to retrieve data from a database without revealing which item is being accessed, thereby preserving query privacy. However, PIR protocols also…
User profiling is crucial in providing personalised services, as it relies on analysing user behaviour and preferences to deliver targeted services. This approach enhances user experience and promotes heightened engagement. Nevertheless,…
Digital identity is a multidimensional, multidisciplinary, and a complex concept. As a result, it is difficult to apprehend. Many contributions have proposed definitions and representations of digital identity. However, lots of them are…
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…
We introduce the notion of a database system that is information theoretically "Secure In Between Accesses"--a database system with the properties that 1) users can efficiently access their data, and 2) while a user is not accessing their…
Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems…
Research use of sensitive information -- personally identifiable information (PII), protected health information (PHI), commercial or proprietary data, and the like -- is increasing as researchers' skill with "big data" matures. Duke…
With the advent of numerous online content providers, utilities and applications, each with their own specific version of privacy policies and its associated overhead, it is becoming increasingly difficult for concerned users to manage and…
Since being proposed in 2006, differential privacy has become a standard method for quantifying certain risks in publishing or sharing analyses of sensitive data. At its heart, differential privacy measures risk in terms of the differences…
Users share a vast amount of data while using web and mobile applications. Most service providers such as email and social media providers provide users with privacy controls, which aim to give users the means to control what, how, when,…
Information personalization is fertile ground for application of AI techniques. In this article I relate personalization to the ability to capture partial information in an information-seeking interaction. The specific focus is on…
In this paper we define the notion of a privacy design strategy. These strategies help IT architects to support privacy by design early in the software development life cycle, during concept development and analysis. Using current data…
Revolution in the area of information technology has brought about changes in many spheres of life. Today, information systems are being used in very sensitive areas such as defence and missile control systems, nuclear plants, etc. Not only…
Nowadays, there are billions interconnected devices forming Cyber-Physical Systems, Internet of Things (IoT) and Industrial Internet of Things (IIoT) ecosystems. With an increasing number of devices and systems in use, amount and the value…
Since the beginning of the Internet thirty years ago, we have witnessed a number of changes in the application of communication technologies. Today, the Internet can be described to a large extent as a ubiquitous infrastructure that is…
OpenData movement around the globe is demanding more access to information which lies locked in public or private servers. As recently reported by a McKinsey publication, this data has significant economic value, yet its release has…
Privacy of the outsourced data is one of the major challenge.Insecurity of the network environment and untrustworthiness of the service providers are obstacles of making the database as a service.Collection and storage of personally…
Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be…
Language Models (LMs) have been shown to leak information about training data through sentence-level membership inference and reconstruction attacks. Understanding the risk of LMs leaking Personally Identifiable Information (PII) has…