The Melbourne Shuffle: Improving Oblivious Storage in the Cloud

We present a simple, efficient, and secure data-oblivious randomized shuffle algorithm. This is the first secure data-oblivious shuffle that is not based on sorting. Our method can be used to improve previous oblivious storage solutions for network-based outsourcing of data

Security by Spatial Reference:Using Relative Positioning to Authenticate Devices for Spontaneous Interaction

Spontaneous interaction is a desirable characteristic associated with mobile and ubiquitous computing. The aim is to enable users to connect their personal devices with devices encountered in their environment in order to take advantage of interaction opportunities in accordance with their situation. However, it is difficult to secure spontaneous interaction as this requires authentication of the encountered device, in the absence of any prior knowledge of the device. In this paper we present a method for establishing and securing spontaneous interactions on the basis of emphspatial references that capture the spatial relationship of the involved devices. Spatial references are obtained by accurate sensing of relative device positions, presented to the user for initiation of interactions, and used in a peer authentication protocol that exploits a novel mechanism for message transfer over ultrasound to ensures spatial authenticity of the sender

Privacy Enhanced Access Control for Outsourced Data Sharing

Traditional access control models often assume that the entity enforcing access control policies is also the owner of data and resources. This assumption no longer holds when data is outsourced to a third-party storage provider, such as the cloud. Existing access control solutions mainly focus on preserving confidentiality of stored data from unauthorized access and the storage provider. However, in this setting, access control policies as well as users' access patterns also become privacy sensitive information that should be protected from the cloud. We propose a two-level access control scheme that combines coarse-grained access control enforced at the cloud, which allows to get acceptable communication overhead and at the same time limits the information that the cloud learns from his partial view of the access rules and the access patterns, and fine-grained cryptographic access control enforced at the user's side, which provides the desired expressiveness of the access control policies. Our solution handles both read and write access control

Euclidean Greedy Drawings of Trees

Greedy embedding (or drawing) is a simple and efficient strategy to route messages in wireless sensor networks. For each source-destination pair of nodes s, t in a greedy embedding there is always a neighbor u of s that is closer to t according to some distance metric. The existence of greedy embeddings in the Euclidean plane R^2 is known for certain graph classes such as 3-connected planar graphs. We completely characterize the trees that admit a greedy embedding in R^2. This answers a question by Angelini et al. (Graph Drawing 2009) and is a further step in characterizing the graphs that admit Euclidean greedy embeddings.Comment: Expanded version of a paper to appear in the 21st European Symposium on Algorithms (ESA 2013). 24 pages, 20 figure

A New Perspective on Clustered Planarity as a Combinatorial Embedding Problem

The clustered planarity problem (c-planarity) asks whether a hierarchically clustered graph admits a planar drawing such that the clusters can be nicely represented by regions. We introduce the cd-tree data structure and give a new characterization of c-planarity. It leads to efficient algorithms for c-planarity testing in the following cases. (i) Every cluster and every co-cluster (complement of a cluster) has at most two connected components. (ii) Every cluster has at most five outgoing edges. Moreover, the cd-tree reveals interesting connections between c-planarity and planarity with constraints on the order of edges around vertices. On one hand, this gives rise to a bunch of new open problems related to c-planarity, on the other hand it provides a new perspective on previous results.Comment: 17 pages, 2 figure

Achieving Good Angular Resolution in 3D Arc Diagrams

We study a three-dimensional analogue to the well-known graph visualization approach known as arc diagrams. We provide several algorithms that achieve good angular resolution for 3D arc diagrams, even for cases when the arcs must project to a given 2D straight-line drawing of the input graph. Our methods make use of various graph coloring algorithms, including an algorithm for a new coloring problem, which we call localized edge coloring.Comment: 12 pages, 5 figures; to appear at the 21st International Symposium on Graph Drawing (GD 2013

Advances on Testing C-Planarity of Embedded Flat Clustered Graphs

We show a polynomial-time algorithm for testing c-planarity of embedded flat clustered graphs with at most two vertices per cluster on each face.Comment: Accepted at GD '1

Preliminary parametric performance assessment of potential final waste forms for alpha low-level waste at the Idaho National Engineering Laboratory. Revision 1

This report presents a preliminary parametric performance assessment (PA) of potential waste disposal systems for alpha-contaminated, mixed, low-level waste (ALLW) currently stored at the Transuranic Storage Area of INEL. The ALLW, which contains from 10 to 100 nCi/g of transuranic (TRU) radionuclides, is awaiting treatment and disposal. The purpose of this study was to examine the effects of several parameters on the radiological-confinement performance of potential disposal systems for the ALLW. The principal emphasis was on the performance of final waste forms (FWFs). Three categories of FWF (cement, glass, and ceramic) were addressed by evaluating the performance of two limiting FWFs for each category. Performance at five conceptual disposal sites was evaluated to illustrate the effects of site characteristics on the performance of the total disposal system. Other parameters investigated for effects on receptor dose included inventory assumptions, TRU radionuclide concentration, FWF fracture, disposal depth, water infiltration rates, subsurface-transport modeling assumptions, receptor well location, intrusion scenario assumptions, and the absence of waste immobilization. These and other factors were varied singly and in some combinations. The results indicate that compliance of the treated and disposed ALLW with the performance objectives depends on the assumptions made, as well as on the FWF and the disposal site. Some combinations result in compliance, while others do not. The implications of these results for decision making relative to treatment and disposal of the INEL ALLW are discussed. The report compares the degree of conservatism in this preliminary parametric PA against that in four other PAs and one risk assessment. All of the assessments addressed the same disposal site, but different wastes. The report also presents a qualitative evaluation of the uncertainties in the PA and makes recommendations for further study

Indexing Information for Data Forensics

We introduce novel techniques for organizing the indexing structures of how data is stored so that alterations from an original version can be detected and the changed values specifically identified. We give forensic constructions for several fundamental data structures, including arrays, linked lists, binary search trees, skip lists, and hash tables. Some of our constructions are based on a new reduced-randomness construction for nonadaptive combinatorial group testing

Splitting Clusters To Get C-Planarity

In this paper we introduce a generalization of the c-planarity testing problem for clustered graphs. Namely, given a clustered graph, the goal of the S PLIT-C-P LANARITY problem is to split as few clusters as possible in order to make the graph c-planar. Determining whether zero splits are enough coincides with testing c-planarity. We show that S PLIT-C-P LANARITY is NP-complete for c-connected clustered triangulations and for non-c-connected clustered paths and cycles. On the other hand, we present a polynomial-time algorithm for flat c-connected clustered graphs whose underlying graph is a biconnected seriesparallel graph, both in the fixed and in the variable embedding setting, when the splits are assumed to maintain the c-connectivity of the clusters