相关论文: Privacy engineering through obfuscation

Privacy engineering, as an emerging field of research and practice, comprises the technical capabilities and management processes needed to implement, deploy, and operate privacy features and controls in working systems. For that, software…

QoS-based Web service recommendation has recently gained much attention for providing a promising way to help users find high-quality services. To facilitate such recommendations, existing studies suggest the use of collaborative filtering…

Protecting the privacy of data-sets has become hugely important these days. Many real-life data-sets like income data, medical data need to be secured before making it public. However, security comes at the cost of losing some useful…

Personally identifiable information (PII) can find its way into cyberspace through various channels, and many potential sources can leak such information. Data sharing (e.g. cross-agency data sharing) for machine learning and analytics is…

It is becoming increasingly clear that users should own and control their data. Utility providers are also becoming more interested in guaranteeing data privacy. As such, users and utility providers should collaborate in data privacy, a…

Differential privacy is a strong notion for privacy that can be used to prove formal guarantees, in terms of a privacy budget, $\epsilon$, about how much information is leaked by a mechanism. However, implementations of privacy-preserving…

When sensitive information is encoded in data, it is important to ensure the privacy of information when attempting to learn useful information from the data. There is a natural tradeoff whereby increasing privacy requirements may decrease…

Online offerings such as web search, news portals, and e-commerce applications face the challenge of providing high-quality service to a large, heterogeneous user base. Recent efforts have highlighted the potential to improve performance by…

Internet of Things (IoT) and cloud computing together give us the ability to sense, collect, process, and analyse data so we can use them to better understand behaviours, habits, preferences and life patterns of users and lead them to…

Face obfuscation (blurring, mosaicing, etc.) has been shown to be effective for privacy protection; nevertheless, object recognition research typically assumes access to complete, unobfuscated images. In this paper, we explore the effects…

Image data collected in the wild often contains private information such as faces and license plates, and responsible data release must ensure that this information stays hidden. At the same time, released data should retain its usefulness…

We study privacy-utility trade-offs where users share privacy-correlated useful information with a service provider to obtain some utility. The service provider is adversarial in the sense that it can infer the users' private information…

The problem of private information "leakage" (inadvertently or by malicious design) from the myriad large centralized searchable data repositories drives the need for an analytical framework that quantifies unequivocally how safe private…

Privacy has been frequently identified as a main concern for system developers while dealing with/managing personal information. Despite this, most existing work on privacy requirements deals with them as a special case of security…

Ensuring the usefulness of electronic data sources while providing necessary privacy guarantees is an important unsolved problem. This problem drives the need for an analytical framework that can quantify the safety of personally…

Obfuscating a dataset by adding random noises to protect the privacy of sensitive samples in the training dataset is crucial to prevent data leakage to untrusted parties for edge applications. We conduct comprehensive experiments to…

Cloud computing enables users to process and store data remotely on high-performance computers and servers by sharing data over the Internet. However, transferring data to clouds causes unavoidable privacy concerns. Here, we present a…

Due to the pervasiveness of image capturing devices in every-day life, images of individuals are routinely captured. Although this has enabled many benefits, it also infringes on personal privacy. A promising direction in research on…

Profiling users for the purpose of targeted advertisements or other kinds of personalization is very popular on the internet. But besides the benefits of individually tailored news feeds and shopping recommendation research has shown that…

The tension between persuasion and privacy preservation is common in real-world settings. Online platforms should protect the privacy of web users whose data they collect, even as they seek to disclose information about these data to…