Related papers: PROPYLA: Privacy Preserving Long-Term Secure Stora…
Deep-learning-as-a-service is a novel and promising computing paradigm aiming at providing machine/deep learning solutions and mechanisms through Cloud-based computing infrastructures. Thanks to its ability to remotely execute and train…
Despite increasing advancements in today's information exchange infrastructure, the preservation of user data and privacy still remains a problem. Both insecure baselines and secure solutions leak user data. For example, Certificate…
Today, large amounts of data are being continuously produced, collected, and exchanged between systems. As the number of devices, systems and data produced grows up, the risk of security breaches increases. This is all the more relevant in…
Transparency - the provision of information about what personal data is collected for which purposes, how long it is stored, or to which parties it is transferred - is one of the core privacy principles underlying regulations such as the…
Access to diverse, high-quality datasets is crucial for machine learning model performance, yet data sharing remains limited by privacy concerns and competitive interests, particularly in regulated domains like healthcare. This dynamic…
The increasing popularity of machine learning approaches and the rising awareness of data protection and data privacy presents an opportunity to build truly secure and trustworthy healthcare systems. Regulations such as GDPR and HIPAA…
With the increasing use of online services, the protection of the privacy of users becomes more and more important. This is particularly critical as authentication and authorization as realized on the Internet nowadays, typically relies on…
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…
With the increasing demands for privacy protection, privacy-preserving machine learning has been drawing much attention in both academia and industry. However, most existing methods have their limitations in practical applications. On the…
In the age of cloud computing, cloud users with limited storage can outsource their data to remote servers. These servers, in lieu of monetary benefits, offer retrievability of their clients' data at any point of time. Secure cloud storage…
Learning-augmented data structures use predicted frequency estimates to retrieve frequently occurring database elements faster than standard data structures. Recent work has developed data structures that optimally exploit these frequency…
Minimizing privacy leakage while ensuring data utility is a critical problem to data holders in a privacy-preserving data publishing task. Most prior research concerns only with one type of data and resorts to a single obscuring method,…
Privacy preserving RFID (Radio Frequency Identification) authentication has been an active research area in recent years. Both forward security and backward security are required to maintain the privacy of a tag, i.e., exposure of a tag's…
The Long Term Evolution of UMTS is one of the latest steps in an advancing series of mobile telecommunications systems. Many articles have already been published on the LTE subject but these publications have viewed the subject from…
Archival institutions and programs worldwide work to ensure that the records of governments, organizations, communities, and individuals are preserved for future generations as cultural heritage, as sources of rights, and as vehicles for…
Privacy has gained a growing interest nowadays due to the increasing and unmanageable amount of produced confidential data. Concerns about the possibility of sharing data with third parties, to gain fruitful insights, beset enterprise…
Cloud computing is a powerful and popular information technology paradigm that enables data service outsourcing and provides higher-level services with minimal management effort. However, it is still a key challenge to protect data privacy…
Security issues in processor architectures remain really critical since users and devices continue to share computing as well as networking resources. So, preserving data privacy in such an environment is really a critical concern. We know…
Embedded systems are parts of our daily life and used in many fields. They can be found in smartphones or in modern cars including GPS, light/rain sensors and other electronic assistance mechanisms. These systems may handle sensitive data…
In this paper, we introduce a data capsule model, a self-contained and self-enforcing data container based on emerging self-sovereign identity standards, blockchain, and attribute-based encryption. A data capsule allows for a transparent,…