相关论文: Lightweight and Secure Two-Party Range Queries ove…

Huge diagrams have unique properties for organizations and research, such as client linkages in informal organizations and customer evaluation lattices in social channels. They necessitate a lot of financial assets to maintain because they…

Counting the fraction of a population having an input within a specified interval i.e. a \emph{range query}, is a fundamental data analysis primitive. Range queries can also be used to compute other interesting statistics such as…

Nowadays companies are increasingly adopting the technology ofcloud computing. This technology is subject to a lot of research and continuousadvances are made. The use of cloud computing in the companies advantagessuch as: reducing costs,…

Blockchains provide environments where parties can interact transparently and securely peer-to-peer without needing a trusted third party. Parties can trust the integrity and correctness of transactions and the verifiable execution of…

Modern cloud computing platforms based on virtual machine monitors carry a variety of complex business that present many network security vulnerabilities. At present, the traditional architecture employs a number of security devices at…

Individuals and organizations tend to migrate their data to clouds, especially in a DataBase as a Service (DBaaS) pattern. The major obstacle is the conflict between secrecy and utilization of the relational database to be outsourced. We…

Data encryption limits the power and efficiency of queries. Direct processing of encrypted data should ideally be possible to avoid the need for data decryption, processing, and re-encryption. It is vital to keep the data searchable and…

With the help of a shared pool of reconfigurable computing resources, clients of the cloud-based model can keep sensitive data remotely and access the apps and services it offers on-demand without having to worry about maintaining and…

In recent years, there is an emerging trend that some computing services are moving from cloud to the edge of the networks. Compared to cloud computing, edge computing can provide services with faster response, lower expense, and more…

Cloud computing is a complex infrastructure of software, hardware, processing, and storage that is available as a service. Cloud computing offers immediate access to large numbers of the world's most sophisticated supercomputers and their…

A growing number of devices and services collect detailed time series data that is stored in the cloud. Protecting the confidentiality of this vast and continuously generated data is an acute need for many applications in this space. At the…

Side-channel information leakage is a known limitation of SGX. Researchers have demonstrated that secret-dependent information can be extracted from enclave execution through page-fault access patterns. Consequently, various recent research…

Storing data in the cloud poses a number of privacy issues. A way to handle them is supporting data replication and distribution on the cloud via a local, centrally synchronized storage. In this paper we propose to use an in-memory RDBMS…

The Domain Name System (DNS) does not provide query privacy. Query obfuscation schemes have been proposed to overcome this limitation, but, so far, they have not been evaluated in a realistic setting. In this paper we evaluate the security…

In todays security landscape, every user wants to access large amounts of data with confidentiality and authorization. To maintain confidentiality, various researchers have proposed several techniques. However, to access secure data,…

In this paper, we propose new location privacy preserving schemes for database-driven cognitive radio networks that protect secondary users' (SUs) location privacy while allowing them to learn spectrum availability in their vicinity. Our…

Due to the increasing demand for cloud services and the threat of privacy invasion, the user is suggested to encrypt the data before it is outsourced to the remote server. The safe storage and efficient retrieval of d-dimensional data on an…

Deep neural networks are increasingly being used in a variety of machine learning applications applied to rich user data on the cloud. However, this approach introduces a number of privacy and efficiency challenges, as the cloud operator…

The vast storage capacity and computational power of cloud servers have led to the widespread outsourcing of machine learning inference services. While offering significant operational benefits, this practice also introduces privacy risks,…

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…