Oblivious Random Access Machine (ORAM) allows a client to hide the access pattern when accessing sensitive data on a remote server. It is known that there exists a logarithmic communication lower bound on any passive ORAM construction, where the server only acts as the storage service. This overhead, however, was shown costly for some applications. Several active ORAM schemes with server computation have been proposed to overcome this limitation. However, they mostly rely on costly homomorphic encryptions, whose performance is worse than passive ORAM. In this article, we propose S3ORAM, a new multi-server ORAM framework, which features
V-Mail: 3D-Enabled Correspondence About Spatial Data on (Almost) All Your Devices
We present V-Mail, a framework of cross-platform applications, interactive techniques, and communication protocols for improved multi-person correspondence about spatial 3D datasets. Inspired by the daily use of e-mail, V-Mail seeks to enable a similar style of rapid, multi-person communication accessible on any device; however, it aims to do this in the new context of spatial 3D communication, where limited access to 3D graphics hardware typically prevents such communication. The approach integrates visual data storytelling with data exploration, spatial annotations, and animated transitions. V-Mail “data stories” are exported in a standard video file format to establish a common baseline level of access on (almost) any device. The V-Mail framework also includes a series of complementary client applications and plugins that enable different degrees of story co-authoring and data exploration, adjusted automatically to match the capabilities of various devices. A lightweight, phone-based V-Mail app makes it possible to annotate data by adding captions to the video. These spatial annotations are then immediately accessible to team members running high-end 3D graphics visualization systems that also include a V-Mail client, implemented as a plugin. Results and evaluation from applying V-Mail to assist communication within an interdisciplinary science team studying Antarctic ice sheets confirm the utility of the asynchronous, cross-platform collaborative framework while also highlighting some current limitations and opportunities for future work.
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- Award ID(s):
- 1704604
- PAR ID:
- 10541278
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE Transactions on Visualization and Computer Graphics
- Volume:
- 30
- Issue:
- 4
- ISSN:
- 1077-2626
- Page Range / eLocation ID:
- 1853 to 1867
- Subject(s) / Keyword(s):
- Data visualization Three-dimensional displays Annotations Spatial databases Collaboration Software Task analysis
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Oblivious Random Access Machine (ORAM) allows a client to hide the access pattern and thus, offers a strong level of privacy for data outsourcing. An ideal ORAM scheme is expected to offer desirable properties such as low client bandwidth, low server computation overhead, and the ability to compute over encrypted data. S3ORAM (CCS’17) is an efficient active ORAM scheme, which takes advantage of secret sharing to provide ideal properties for data outsourcing such as low client bandwidth, low server computation and low delay. Despite its merits, S3ORAM only offers security in the semi-honest setting. In practice, an ORAM protocol is likely to operate in the presence of malicious adversaries who might deviate from the protocol to compromise the client privacy. In this paper, we propose MACAO, a new multi-server ORAM framework, which offers integrity, access pattern obliviousness against active adversaries, and the ability to perform secure computation over the accessed data. MACAO harnesses authenticated secret sharing techniques and tree-ORAM paradigm to achieve low client communication, efficient server computation, and low storage overhead at the same time. We fully implemented MACAO and conducted extensive experiments in real cloud platforms (Amazon EC2) to validate the performance of MACAO compared with the state-of-the-art. Our results indicate that MACAO can achieve comparable performance to S3ORAM while offering security against malicious adversaries. MACAO is a suitable candidate for integration into distributed file systems with encrypted computation capabilities towards enabling an oblivious functional data outsourcing infrastructure.more » « less
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TVCG.2022.3229017
