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Terrorist fraud is an attack against distance bounding protocols, whereby a malicious prover allows an adversary to authenticate on their behalf without revealing their secret key. In this paper, we propose new attack strategies that lead to successful terrorist frauds on proven-secure protocols.

Most research modelling Bitcoin-style decentralised consensus protocols has assumed profit-motivated participants. Complementary to this analysis, we revisit the notion of attackers with an extrinsic motivation to disrupt the consensus process (Goldfinger attacks). We outline several routes for obtaining a majority of decision-making power in the consensus protocol (a hostile takeover). Our analysis suggests several fundamental differences between proof-of-work and proof-of-stake systems in the face of such an adversary.

Part 8: Pattern Recognition and Image Processing; International audience; Paper-based documents are important and still widely used in government agencies and private entities as some documents cannot be replaced by electronic documents. These include loan agreements, dispatch or contracts, household registrations and passports. They must be paper-based. Paper-based documents can be easily forged with a printer and a scanner, and imaging software can easily edit them. This paper presents a paper-based document authentication by applying a digital signature and HC2D barcode to verify the integrity of the text message and the sender of the document. This is useful both for a quick inspection of documents with large quantities and monitoring that may help prevent fraud and forgery which may have occurred.

Consumers are often willing to contribute their personal data for analytics projects that may create new insights into societal problems. However, consumers also have justified privacy concerns about the release of their data.

This paper presents the results from a tertiary entrance test that was delivered to two groups of candidates, one as a paper based test and the other as a computer based test. Item level differential reveals a pattern that appears related to item type: questions based on diagrammatic stimulus show a pattern of increased difficulty when delivered on computer. Differential in performance was not present in other sections of the test and it would appear unlikely to be explained by demographic differences between the groups. It is suggested this differential is due to the inability of the candidates to freely annotate on the stimulus when delivered on computer screen. More work needs to be done on considering the role of annotation as a problem solving strategy in high-stakes testing, in particular with certain kinds of stimulus, such as diagrams.

Over several decades, a large body of research has been established that focuses on Pen-and-Paper Computing. This chapter reviews previous work of the field – both from a technological and interface perspective – and discusses future directions of research and development.

Identifying the natural gestures for a tabletop application is one of the most challenging tasks developers must accomplish in order to achieve a good system user interface. This problem is even more difficult in a collaborative environment. Cooperative Gestures allow richer interaction and must be evaluated when designing a new multi-user tabletop interface. In this paper we present the use of paper prototyping to analyze user interaction on a tabletop collaborative game application. Our results show that it is possible to extract natural gestures for an application using this technique, regardless of some limitations.

Personal Digital Assistants (PDAs) are a viable technology for providing access to Electronic Medical Records at the point-of-care. However, acceptance of this technology by clinicians will depend on how easy they can make the transition from the system they normally use to a PDA-based system. Since many hospitals are still using paper-based patient record systems this study intends to provide some insight on the aspects that need to be considered in the transition from a paper-based system to a PDA-based system. The study compares the interaction of nurses with PDA-based and paper-based nursing documentation systems in terms of performance and subjective satisfaction. Twenty staff nurses from a metropolitan hospital performed twelve tasks on each system. The study supports the conclusion that a PDA-based nursing documentation system can be superior to a paper-based system in term of performance for tasks that don't required writing notes. Nurses were significantly more satisfied with the PDA-based system than with the paper-based system with every interaction and system aspect evaluated on the study. In general the results of the study provide hard evidence to predict an easy transition for nurses from a paper-based system to a PDA-based system nursing documentation system.

This paper proposes a novel system which automatically extracts the intended items to buy from a hand written shopping list. This intelligent shopping list relies on an ontology of the products which is provided by the shopping mall. In our scenario the shopping list is written on digital Anoto paper. After transmitting the hand written strokes to the computer, the list items are recognized by a hand writing recognition system. Next, the recognized text is parsed in order to detect the amount and the desired item. This is then matched to the underlying ontology and the intended order is recognized. Our current prototype works on an ontology of 300 products. In our real-world experiments we asked 20 persons to write shopping lists without any constrains.

In this paper we show how privacy of genomic sequences can be protected while they are analyzed using Hidden Markov Models (HMM), which is commonly done in bioinformatics to detect certain non-beneficial patterns in the genome. Besides offering strong privacy guarantees, our solution also allows protecting the intellectual property of the parties involved, which makes the solution viable for implementation of secure bioinformatics services. In particular, we show how two mutually mistrusting parties can obliviously run the forward algorithm in a setup where one party knows a HMM and another party knows a genomic string; while the parties learn whether the model fits the genome, they neither have to disclose the parameterization of the model nor the sequence to each other. Despite the huge number of arithmetic operations required to solve the problem, we experimentally show that HMMs with sizes of practical importance can obliviously be evaluated using computational resources typically found in medical laboratories. As a central technical contribution, we give improved protocols for secure and numerically stable computations on non-integer values.