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Cloud computing is a most adopted emerging technology by all organizations. Data storage and sharing of data in cloud is the most used services, whereas secure public auditing makes challenge in such services. Since cloud infrastructure which is not a trustable, users in the group for data sharing must compute their signatures and shares their block for integrity auditing. Any corruption, insider...
Personal information is often gathered and processed in a decentralized fashion. Examples include health records and governmental data bases. To protect the privacy of individuals, no unique user identifier should be used across the different databases. At the same time, the utility of the distributed information needs to be preserved which requires that it be nevertheless possible to link different...
In cloud services, deduplication technology is commonly used to reduce the space and bandwidth requirements of services by eliminating redundant data and storing only a single copy. Deduplication is most effective when multiple users outsource the same data to the cloud storage, but it raises issues relating to security and ownership. Proof-ofownership schemes allow any owner of the same data to prove...
Image sharing is one of the most attractive features facilitated by different social media sites such as Facebook, Flickr, Pinterest, and Instagram. People frequently use these social media sites to express various aspects of their life with peers they are connected through these sites. The service providers of these sites sometimes use the image features for social discovery such as friend recommendation,...
Outsourcing data and computation to cloud server provides a cost-e ective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing...
Opportunistic Network (OppNet) is an emerging communication paradigm, by which nodes inside forward messages through personal contact opportunities. Recently, numerous studies have focused on predicting nodes meeting to promote routing efficiency and reduce transmission delay. However, individual privacy would likely be revealed to strangers or attackers during the execution of prediction. In this...
Mobile crowd-sourcing can become as a strategy to perform time-sensitive urban tasks (such as municipal monitoring and last mile logistics) by effectively coordinating smartphone users. The success of the mobile crowd-sourcing platform depends mainly on its effectiveness in engaging crowd-workers, and recent studies have shown that compared to the pull-based approach, which relies on crowd-workers...
Preserving user privacy is crucial for the wide adoption of crowdsensing and participatory sensing applications that rely on personal devices. Currently, each application comes with its own hardwired and possibly undocumented privacy support (if any), while the horizontal protection mechanisms provided by operating and runtime systems operate at a low level that can significantly harm application...
The popularity of mobile devices with positioning capability and Internet accessibility in recent years has caused a revolution in the Location Based Services (LBS) market. Unfortunately, without preserving the user's location privacy, LBS providers can collect and log the accurate locations of the service users. Many mechanisms have been developed to preserve the LBS user's location privacy. While...
Cloud computing is a powerful service that allows the cloud users to utilize the resources located in the cloud servers by pay-per-use or charge-per-use mode through the internet. The cloud users are enjoying the on-demand services provided by the cloud computing environment without maintaining the data in a local system. Even though the service is offered to cloud users in an efficient way, there...
In this epoch of growing technology the data collected by organizations has the requirement to preserve the privacy of the individuals. The techniques like anonymization, randomization are used to achieve the goal. But unfortunately anonymization leads to certain level of information loss while preserving privacy. Due to drift of data over the centralized server has added to the more demand of preserving...
Companies and other organizations such as hospitals seek more and more to enjoy the benefits of cloud computing in terms of storage space and computing power. However, outsourced data must be encrypted in order to be protected against possible attacks. Therefore, traditional information retrieval systems (IRS) are no longer effective and must be adapted in order to work over encrypted cloud data....
Advance in ICT and convergence technology, latest trend of e-commercial is O2O. Scale of O2O market is growing and famous platform firms start to invest this industry. However, O2O service's security requirements for safe O2O service has not been researched yet. In O2O Service, Data flows from Online to Offline or from Offline to Online, So, Traditional Online Security countermeasures is not appropriate...
Large-scale multimedia data generated in our daily life have increasingly motivated companies and researchers to discover valuable knowledge and hidden information by employing machine learning techniques. It is well known that this is an inherently time consuming job to deal with massive multimedia data locally. Thanks to the rapid development of cloud computing, the data owner is highly motivated...
Recently, cloud-based machine learning (ML) services are getting popular. A client sends input data to a cloud, which performs ML algorithms based on neural networks (NN) using its powerful server, and returns the result back to the client. In this scenario, the server can easily collect the users’ sensitive data, raising the privacy issues and making users reluctant to use the services. This paper...
We propose a new approach to running machine learning (ML) web app on resource-constrained embedded devices by offloading ML computations to servers. We can dynamically offload computations depending on the problem size and network status. The execution state is saved in the form of another web app called snapshot which simplifies the state migration. Some issues related to ML such as how to handle...
Cloud computing is a growing technology that offers compute, storage and network resources as a service over the internet. It enables the individuals, clients or the enterprises to outsource their data and application software to the cloud server. The services are offered by a cloud service provider (CSP) and the users need to pay for what they use. There are many security concerns needs to be addressed...
This fast abstract proposes a privacy-preserving quantum-secure protocol for DBSCAN clustering algorithm. It allows multiple parties to jointly compute clusters without revealing their individual datasets to each other. We show how to outsource the DBSCAN computation on encrypted data to a cloud service provider securely such that the parties do not need to perform the expensive clustering computation...
Over the last five years, on-line analytical processing (OLAP) became one of the essential information processing technologies. OLAP technology has been successfully used in different areas: retail, financial services, telecommunication, health care etc. Because of this security of data stored in Data Warehouses became one of the most important aspect of this technology, especially when we speaking...
Nowadays, large amounts of data are stored with cloud service providers. Third-party auditors (TPAs), with the help of cryptography, are often used to verify this data. However, most auditing schemes don't protect cloud user data from TPAs. A review of the state of the art and research in cloud data auditing techniques highlights integrity and privacy challenges, current solutions, and future research...
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