Quantum one-time programs

A one-time program is a hypothetical device by which a user may evaluate a circuit on exactly one input of his choice, before the device self-destructs. One-time programs cannot be achieved by software alone, as any software can be copied and re-run. However, it is known that every circuit can be compiled into a one-time program using a very basic hypothetical hardware device called a one-time memory. At first glance it may seem that quantum information, which cannot be copied, might also allow for one-time programs. But it is not hard to see that this intuition is false: one-time programs for classical or quantum circuits based solely on quantum information do not exist, even with computational assumptions. This observation raises the question, "what assumptions are required to achieve one-time programs for quantum circuits?" Our main result is that any quantum circuit can be compiled into a one-time program assuming only the same basic one-time memory devices used for classical circuits. Moreover, these quantum one-time programs achieve statistical universal composability (UC-security) against any malicious user. Our construction employs methods for computation on authenticated quantum data, and we present a new quantum authentication scheme called the trap scheme for this purpose. As a corollary, we establish UC-security of a recent protocol for delegated quantum computation.

Count-min sketches for estimating password frequency within Hamming distance two

The count-min sketch is a useful data structure for recording and estimating the frequency of string occurrences, such as passwords, in sub-linear space with high accuracy. However, it cannot be used to draw conclusions on groups of strings that are similar, for example close in Hamming distance. This paper introduces a variant of the count-min sketch which allows for estimating counts within a specified Hamming distance of the queried string. This variant can be used to prevent users from choosing popular passwords, like the original sketch, but it also allows for a more efficient method of analysing password statistics.

A framework for security analysis of key derivation functions

This paper presents a comprehensive formal security framework for key derivation functions (KDF). The major security goal for a KDF is to produce cryptographic keys from a private seed value where the derived cryptographic keys are indistinguishable from random binary strings. We form a framework of five security models for KDFs. This consists of four security models that we propose: Known Public Inputs Attack (KPM, KPS), Adaptive Chosen Context Information Attack (CCM) and Adaptive Chosen Public Inputs Attack(CPM); and another security model, previously defined by Krawczyk [6], which we refer to as Adaptive Chosen Context Information Attack(CCS). These security models are simulated using an indistinguisibility game. In addition we prove the relationships between these five security models and analyse KDFs using the framework (in the random oracle model).

Modeling obligations with event-calculus

Time plays an important role in norms. In this paper we start from our previously proposed classification of obligations, and point out some shortcomings of Event Calculus (EC) to represent obligations. We proposed an extension of EC that avoids such shortcomings and we show how to use it to model the various types of obligations.

Gestural, emergent and expressive : three research themes for haptic interaction

Drawing on three case studies of work in the fields of participatory design, interaction design and electronic arts, we reflect on the implications of these studies for haptic interface research. We propose three themes: gestural; emergent; and expressive; as signposts for a program of research into haptic interaction that could point the way towards novel approaches to haptic interaction and move us from optic to haptic ways of seeing.

The heterogeneous cluster ensemble method using hubness for clustering text documents

We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed meth-od outperforms state-of-the-art text clustering approaches.

The 4C spectrum of fundamental behavioral relations for concurrent systems

The design of concurrent software systems, in particular process-aware information systems, involves behavioral modeling at various stages. Recently, approaches to behavioral analysis of such systems have been based on declarative abstractions defined as sets of behavioral relations. However, these relations are typically defined in an ad-hoc manner. In this paper, we address the lack of a systematic exploration of the fundamental relations that can be used to capture the behavior of concurrent systems, i.e., co-occurrence, conflict, causality, and concurrency. Besides the definition of the spectrum of behavioral relations, which we refer to as the 4C spectrum, we also show that our relations give rise to implication lattices. We further provide operationalizations of the proposed relations, starting by proposing techniques for computing relations in unlabeled systems, which are then lifted to become applicable in the context of labeled systems, i.e., systems in which state transitions have semantic annotations. Finally, we report on experimental results on efficiency of the proposed computations.

Ageing, technology anxiety and intuitive use of complex interfaces

This paper presents the outcome of a study that investigated the relationships between technology prior experience, self-efficacy, technology anxiety, complexity of interface (nested versus flat) and intuitive use in older people. The findings show that, as expected, older people took less time to complete the task on the interface that used a flat structure when compared to the interface that used a complex nested structure. All age groups also used the flat interface more intuitively. However, contrary to what was hypothesised, older age groups did better under anxious conditions. Interestingly, older participants did not make significantly more errors compared with younger age groups on either interface structures.

Awesome foursome? The compatibility of situation awareness across drivers, riders, cyclists, and pedestrians

Collisions between distinct road users (e.g. drivers and motorcyclists) make a substantial contribution to the road trauma burden. Although evidence suggests distinct road users interpret the same road situations differently, it is not clear how road users’ situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study which examined driver, cyclist, motorcyclist and pedestrian situation awareness at intersections. The findings suggest that situation awareness at intersection is markedly different across the four road user groups studied, and that some of these differences may create conflicts between the different road users. The findings also suggest that the causes of the differences identified relate to road design and road user experience. In closing, the key role of road design and training in supporting safe interactions between distinct road users is discussed.

A novel method for finding similarities between unordered trees using matrix data model

Trees are capable of portraying the semi-structured data which is common in web domain. Finding similarities between trees is mandatory for several applications that deal with semi-structured data. Existing similarity methods examine a pair of trees by comparing through nodes and paths of two trees, and find the similarity between them. However, these methods provide unfavorable results for unordered tree data and result in yielding NP-hard or MAX-SNP hard complexity. In this paper, we present a novel method that encodes a tree with an optimal traversing approach first, and then, utilizes it to model the tree with its equivalent matrix representation for finding similarity between unordered trees efficiently. Empirical analysis shows that the proposed method is able to achieve high accuracy even on the large data sets.

Indexing and efficient instance-based retrieval of process models using untanglings

Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process model repositories emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for indexing process models that relies on their alternative representations, called untanglings. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the total executability problem. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.

Reconciling folksonomic tagging with taxa for bioacoustic annotations

Acoustic sensors are increasingly used to monitor biodiversity. They can remain deployed in the environment for extended periods to passively and objectively record the sounds of the environment. The collected acoustic data must be analyzed to identify the presence of the sounds made by fauna in order to understand biodiversity. Citizen scientists play an important role in analyzing this data by annotating calls and identifying species. This paper presents our research into bioacoustic annotation techniques. It describes our work in defining a process for managing, creating, and using tags that are applied to our annotations. This paper includes a detailed description of our methodology for correcting and then linking our folksonomic tags to taxonomic data sources. Providing tools and processes for maintaining species naming consistency is critical to the success of a project designed to generate scientific data. We demonstrate that cleaning the folksonomic data and providing links to external taxonomic authorities enhances the scientific utility of the tagging efforts of citizen scientists.

Adapting Lyubashevsky's signature schemes to the ring signature setting

Basing signature schemes on strong lattice problems has been a long standing open issue. Today, two families of lattice-based signature schemes are known: the ones based on the hash-and-sign construction of Gentry et al.; and Lyubashevsky’s schemes, which are based on the Fiat-Shamir framework. In this paper we show for the first time how to adapt the schemes of Lyubashevsky to the ring signature setting. In particular we transform the scheme of ASIACRYPT 2009 into a ring signature scheme that provides strong properties of security under the random oracle model. Anonymity is ensured in the sense that signatures of different users are within negligible statistical distance even under full key exposure. In fact, the scheme satisfies a notion which is stronger than the classical full key exposure setting as even if the keypair of the signing user is adversarially chosen, the statistical distance between signatures of different users remains negligible. Considering unforgeability, the best lattice-based ring signature schemes provide either unforgeability against arbitrary chosen subring attacks or insider corruption in log-sized rings. In this paper we present two variants of our scheme. In the basic one, unforgeability is ensured in those two settings. Increasing signature and key sizes by a factor k (typically 80 − 100), we provide a variant in which unforgeability is ensured against insider corruption attacks for arbitrary rings. The technique used is pretty general and can be adapted to other existing schemes.

Structured feature extraction using association rules

As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

Overview of INEX 2013

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2013 evaluation campaign, which consisted of four activities addressing three themes: searching professional and user generated data (Social Book Search track); searching structured or semantic data (Linked Data track); and focused retrieval (Snippet Retrieval and Tweet Contextualization tracks). INEX 2013 was an exciting year for INEX in which we consolidated the collaboration with (other activities in) CLEF and for the second time ran our workshop as part of the CLEF labs in order to facilitate knowledge transfer between the evaluation forums. This paper gives an overview of all the INEX 2013 tracks, their aims and task, the built test-collections, and gives an initial analysis of the results