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Trusted timestamping is a process for proving that certain information existed at a given point in time. This paper presents a trusted timestamping concept and its implementation in form of a web-based service that uses the decentralized…
Differential privacy (DP) has steadily become the de-facto standard for achieving privacy in data analysis, which is typically implemented either in the "central" or "local" model. The local model has been more popular for commercial…
Blockchain technologies have been boosting the development of data-driven decentralized services in a wide range of fields. However, with the spirit of full transparency, many public blockchains expose all types of data to the public such…
Privacy Security of data in Cloud Storage is one of the main issues. Many Frameworks and Technologies are used to preserve data security in cloud storage. [1] Proposes a framework which includes the design of data organization structure,…
Due to HIPAA and other privacy regulations, it is imperative to maintain patient privacy while conducting research on patient health records. In this paper, we propose AegisBlock, a patient-centric access controlled framework to share…
Multi-access Edge Computing (MEC), an enhancement of 5G, processes data closer to its generation point, reducing latency and network load. However, the distributed and edge-based nature of 5G-MEC presents privacy and security challenges,…
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 popularity of the cloud, clients oursource their data to clouds in order to take advantage of unlimited virtualized storage space and the low management cost. Such trend prompts the privately oursourcing computation,…
Cryptocurrencies are poised to revolutionize the modern economy by democratizing commerce. These currencies operate on top of blockchain-based distributed ledgers. Existing permissionless blockchain-based protocols offer unparalleled…
Off-grid networks are recently emerging as a solution to connect the unconnected or provide alternative services to networks of possibly untrusted participants. The systems currently used, however, exhibit limitations due to their…
As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and…
Decentralised cloud computing platforms enable individuals to offer and rent resources in a peer-to-peer fashion. They must assign resources from multiple sellers to multiple buyers and derive prices that match the interests and capacities…
The ability to perform computations on encrypted data is a powerful tool for protecting privacy. Recently, protocols to achieve this on classical computing systems have been found. Here we present an efficient solution to the quantum…
A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures. In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often…
This paper explores the integration of advanced cryptographic techniques for secure computation in data spaces to enable secure and trusted data sharing, which is essential for the evolving data economy. In addition, the paper examines the…
Non-orthogonal multiple access (NOMA) with successive interference cancellation receiver is considered as one of the most potent multiple access techniques to be adopted in future wireless communication networks. Data security in the NOMA…
Network-level privacy is the Achilles heel of financial privacy in cryptocurrencies. Financial privacy amounts to achieving and maintaining blockchain- and network-level privacy. Blockchain-level privacy recently received substantial…
NeuraCrypt (Yara et al. arXiv 2021) is an algorithm that converts a sensitive dataset to an encoded dataset so that (1) it is still possible to train machine learning models on the encoded data, but (2) an adversary who has access only to…
The security of blockchain systems is fundamentally based on the decentralized consensus in which the majority of parties behave honestly, and the content verification process is essential to maintaining the robustness of blockchain…
Federated knowledge discovery and data mining are challenged to assess the trustworthiness of data originating from autonomous sources while protecting confidentiality and privacy. Truth-finding algorithms help corroborate data from…