Data access

About: Data access is a research topic. Over the lifetime, 13141 publications have been published within this topic receiving 172859 citations. The topic is also known as: Data access.

A Secure Client Side Deduplication Scheme in Cloud Storage Environments

Abstract: Recent years have witnessed the trend of leveraging cloud-based services for large scale content storage, processing, and distribution. Security and privacy are among top concerns for the public cloud environments. Towards these security challenges, we propose and implement, on OpenStack Swift, a new client-side deduplication scheme for securely storing and sharing outsourced data via the public cloud. The originality of our proposal is twofold. First, it ensures better confidentiality towards unauthorized users. That is, every client computes a per data key to encrypt the data that he intends to store in the cloud. As such, the data access is managed by the data owner. Second, by integrating access rights in metadata file, an authorized user can decipher an encrypted file only with his private key.

Method and system for providing remote access to resources in a secure data center over a network

Abstract: Methods, computer products, and systems are described for providing remote access to resources in a secure data center protected by at least one firewall. One method includes sending by an internal server within the secure data center a request to an external server outside of the secure data center to establish a secure data transport channel between the internal server and the external server. The request travels through at least one firewall protecting the secure data center and over a public network, a private network, and/or a second firewall. The internal server receives a reply to the request from the external server granting the request and confirming the establishment of the secure data transport channel. When a first message from the external server instructing the internal server to create a first data access point associated with a first session is received via the established secure data transport channel, the internal server instantiates the first data access point for the first session and visual data corresponding to the resources in the secure data center is sent from the first data access point to the external server via the secure data transport channel. The visual data is received by the external server and then sent to a first client associated with the first session so that the first client is provided visual access to the resources in the secure data center while the resources remain protected within the secure data center.

Method of pre-caching or pre-fetching data utilizing thread lists and multimedia editing systems using such pre-caching

Abstract: A method of pre-caching data using thread lists, and a multi-media editing system using such a pre-caching method, are disclosed. A list of data which will be required by a host application is passed to a data storage device such as a hard disk drive, CDROM drive, or other data storage device. The data storage device locates the data and stores it in its own storage device buffer. Thus, the data is immediately available when requested by the host. The pre-caching method may be used in a multimedia or video editing system to quickly retrieve data from storage devices. The thread list may include a video thread, an audio thread and a data access parameter reflecting host data application requirements. The data access parameter may include at least one of data prioritization, cache management, error processing including resend capability, and data supply rate. The thread list may also include data specifying a percentage of the storage device buffer to be reserved for read ahead data and a percentage of the storage device buffer to be reserved for data which has been previously provided to the host computer.

Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

Abstract: Limited data access is a longstanding barrier to data-driven research and development in the networked systems community. In this work, we explore if and how generative adversarial networks (GANs) can be used to incentivize data sharing by enabling a generic framework for sharing synthetic datasets with minimal expert knowledge. As a specific target, our focus in this paper is on time series datasets with metadata (e.g., packet loss rate measurements with corresponding ISPs). We identify key challenges of existing GAN approaches for such workloads with respect to fidelity (e.g., long-term dependencies, complex multidimensional relationships, mode collapse) and privacy (i.e., existing guarantees are poorly understood and can sacrifice fidelity). To improve fidelity, we design a custom workflow called DoppelGANger (DG) and demonstrate that across diverse real-world datasets (e.g., bandwidth measurements, cluster requests, web sessions) and use cases (e.g., structural characterization, predictive modeling, algorithm comparison), DG achieves up to 43% better fidelity than baseline models. Although we do not resolve the privacy problem in this work, we identify fundamental challenges with both classical notions of privacy and recent advances to improve the privacy properties of GANs, and suggest a potential roadmap for addressing these challenges. By shedding light on the promise and challenges, we hope our work can rekindle the conversation on workflows for data sharing.