Related papers: Personal Information Databases
Differential privacy is a notion of privacy that has become very popular in the database community. Roughly, the idea is that a randomized query mechanism provides sufficient privacy protection if the ratio between the probabilities of two…
If the information system is intruded or attacked by hackers, leaked personal data or serious economic loss may occur; the threats may be serious security problems. For security services, information security certification is built based on…
Breached data refers to the unauthorized access, theft, or exposure of confidential or sensitive information. Breaches typically occur when malicious actors or unauthorized users breach secure systems or networks, resulting in compromised…
In this work, we propose the first framework for integrating Differential Privacy (DP) and Contextual Integrity (CI). DP is a property of an algorithm that injects statistical noise to obscure information about individuals represented…
Owing to recorded incidents of Information technology inclined organisations failing to respond effectively to threat incidents, this project outlines the benefits of conducting a comprehensive risk assessment which would aid proficiency in…
In two-party machine learning prediction services, the client's goal is to query a remote server's trained machine learning model to perform neural network inference in some application domain. However, sensitive information can be obtained…
Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains difficult: PII spans are heterogeneous, locale-dependent, context-sensitive, and often…
Differential privacy is a recent notion of privacy for statistical databases that provides rigorous, meaningful confidentiality guarantees, even in the presence of an attacker with access to arbitrary side information. We show that for a…
Current architectures to validate, certify, and manage identity are based on centralised, top-down approaches that rely on trusted authorities and third-party operators. We approach the problem of digital identity starting from a human…
We present a novel framework, called Private Disclosure of Information (PDI), which is aimed to prevent an adversary from inferring certain sensitive information about subjects using the data that they disclosed during communication with an…
Retrieving up-to-date information from a publicly accessible database poses significant threats to the user's privacy. {\em Private information retrieval} (PIR) protocols allow a user to retrieve any entry from a database, without revealing…
In the current paradigm of digital personalized services, the centralized management of personal data raises significant privacy concerns, security vulnerabilities, and diminished individual autonomy over sensitive information. Despite…
We provide an overview of PSI ("a Private data Sharing Interface"), a system we are developing to enable researchers in the social sciences and other fields to share and explore privacy-sensitive datasets with the strong privacy protections…
Cyber Threat Intelligence (CTI) sharing is an important activity to reduce information asymmetries between attackers and defenders. However, this activity presents challenges due to the tension between data sharing and confidentiality, that…
Sanitizing sensitive text data typically involves removing personally identifiable information (PII) or generating synthetic data under the assumption that these methods adequately protect privacy; however, their effectiveness is often only…
Information privacy has gained increased attention in recent years. This paper focuses on a particular aspect of privacy, i.e., personal information privacy. In this paper a conceptual framework is developed based Westin's theory of…
While a number of data privacy techniques have been proposed in the recent years, a few frameworks have been suggested for the implementation of the data privacy process. Most of the proposed approaches are tailored towards implementing a…
Many datasets contain personally identifiable information, or PII, which poses privacy risks to individuals. PII masking is commonly used to redact personal information such as names, addresses, and phone numbers from text data. Most modern…
Password-authenticated identities, where users establish username-password pairs with individual servers and use them later on for authentication, is the most widespread user authentication method over the Internet. Although they are…
Ubiquitous deployment of low-cost smart devices and widespread use of high-speed wireless networks have led to the rapid development of the Internet of Things (IoT). IoT embraces countless physical objects that have not been involved in the…