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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.

Writing on the board is an important part of a lecture. Lecturers’ handwriting is not always perfect. Usually, a lecturer can write slower and more legibly, this will increase understandability but slow down the lecture. In this chapter, we analyze an optimal trade-off between speed and legibility.

The aim of this paper is to examine generic competition in the UK, with a special focus on the role of Health Technology Assessment (HTA) on generic market entry and diffusion. In the UK, where no direct price regulation on pharmaceuticals exists, HTA has a leading role for recommending the use of medicines providing a non-regulatory aspect that may influence the dynamics in the generic market. The paper focuses on the role of Technology Appraisals issued by the National Institute for Health and Care Excellence (NICE). We follow a two-step approach. First, we examine the probability of generic entry. Second, conditional on generic entry, we examine the determinants of generic market share. We use data from IQVIA British Pharmaceutical Index (BPI) for the primary care market for 60 products that lost patent between 2003 and 2012. Our results suggest that market size remains one of the main drivers of generic entry. After controlling for market size, intermolecular substitution and difficulty of manufacturing increase the likelihood of generic entry. After generic entry, our estimates suggest that generic market share is highly state dependent. Our findings also suggest that while NICE recommendations do influence generic uptake, there is only marginal evidence they affect generic entry.

In this paper, linear regression (LR), multi-linear regression (MLR) and polynomial regression (PR) techniques are applied to propose a model Li-MuLi-Poly. The model predicts COVID-19 deaths happening in the United States of America. The experiment was carried out on machine learning model, minimum mean square error model, and maximum likelihood ratio model. The best-fitting model was selected according to the measures of mean square error, adjusted mean square error, mean square error, root mean square error (RMSE) and maximum likelihood ratio, and the statistical t-test was used to verify the results. Data sets are analyzed, cleaned up and debated before being applied to the proposed regression model. The correlation of the selected independent parameters was determined by the heat map and the Carl Pearson correlation matrix. It was found that the accuracy of the LR model best-fits the dataset when all the independent parameters are used in modeling, however, RMSE and mean absolute error (MAE) are high as compared to PR models. The PR models of a high degree are required to best-fit the dataset when not much independent parameter is considered in modeling. However, the PR models of low degree best-fits the dataset when independent parameters from all dimensions are considered in modeling.

Engaging deep neural networks for textual sentiment analysis is an extensively practiced domain of research. Textual sentiment classification harnesses the full computational potential of deep learning models. Typically, these research works are carried either with a popular open-source data corpus, or self-extracted short phrase texts from Twitter, Reddit, or web-scrapped text data from other resources. Rarely do we see a large amount of data on a current ongoing event is being collected and cultured further. Also, an even more complex task would be to model the data from a currently ongoing event, not only for scaling the sentiment accuracy but also for making a predictive analysis for the same. In this paper, we propose a novel approach for achieving sentiment evaluation accuracy by using a deep neural network on live-streamed tweets on Coronavirus and future case growth prediction. We develop a large tweet corpus exclusively based on the Coronavirus tweets. We split the data into train and test sets, alongside we perform polarity classification and trend analysis. The refined outcome from the trend analysis helps to train the data to provide an incremental learning curvature for our neural network, and we obtain an accuracy of 90.67%. Finally, we provide a statistical-based future prediction for Coronavirus cases growth. Not only our model outperforms several previous state-of-art experiments in overall sentiment accuracy comparison for similar tasks, but it also maintains a throughout performance stability among all the test cases when tested with several popular open-source text corpora.

This paper concerns blind signature schemes. We focus on two moves constructions, which imply concurrent security. There are known efficient blind signature schemes based on the random oracle model and on the common reference string model. However, constructing two move blind signatures in the standard model is a challenging task, as shown by the impossibility results of Fischlin et al. The recent construction by Garg et al. (Eurocrypt’14) bypasses this result by using complexity leveraging, but it is impractical due to the signature size (\(\approx \) 100 kB). Fuchsbauer et al. (Crypto’15) presented a more practical construction, but with a security argument based on interactive assumptions. We present a blind signature scheme that is two-move, setup-free and comparable in terms of efficiency with the results of Fuchsbauer et al. Its security is based on a knowledge assumption.

Most electronic payment systems for applications, such as eTicketing and eToll, involve a single entity acting as both merchant and bank. In this paper, we propose an efficient privacy-preserving post-payment eCash system suitable for this particular use case that we refer to, afterwards, as private eCash. To this end, we introduce a new partially blind signature scheme based on a recent Algebraic MAC scheme due to Chase et al. Unlike previous constructions, it allows multiple presentations of the same signature in an unlinkable way. Using it, our system is the first versatile private eCash system where users must only hold a sole reusable token (i.e. a reusable coin spendable to a unique merchant). It also enables identity and token revocations as well as flexible payments. Indeed, our payment tokens are updated in a partially blinded way to collect refunds without invading user’s privacy. By implementing it on a Global Platform compliant SIM card, we show its efficiency and suitability for real-world use cases, even for delay-sensitive applications and on constrained devices as a transaction can be performed in only 205 ms.

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.

Smart mobile devices process and store a vast amount of security- and privacy-sensitive data. To protect this data from malicious applications mobile operating systems, such as Android, adopt fine-grained access control architectures. However, related work has shown that these access control architectures are susceptible to application-layer privilege escalation attacks. Both automated static and dynamic program analysis promise to proactively detect such attacks. Though while state-of-the-art static analysis frameworks cannot adequately address native and highly obfuscated code, dynamic analysis is vulnerable to malicious applications using logic bombs to avoid early detection.

The most common method for a user to gain access to a system, service, or resource is to provide a secret, often a password, that verifies her identity and thus authenticates her. Password-based authentication is considered strong only when the password meets certain length and complexity requirements, or when it is combined with other methods in multi-factor authentication. Unfortunately, many authentication systems do not enforce strong passwords due to a number of limitations; for example, the time taken to enter complex passwords. We present an authentication system that addresses these limitations by prompting a user for credentials once and then storing an authentication ticket in a wearable device that we call Kerberos Bracelet Identification (KBID).

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.

Peer-to-peer (P2P) networks support a wide variety of network services including elastic services such as file-sharing and downloading and inelastic services such as real-time multiparty conferencing. Each peer who acquires a service will receive a certain level of satisfaction if the service is provided with a certain amount of resource. The utility function is used to describe the satisfaction of a peer when acquiring a service. In this paper we consider optimal resource allocation for elastic and inelastic services and formulate a utility maximization model which is an intractable and difficult non-convex optimization problem. In order to resolve it, we apply the successive approximation method and approximate the non-convex problem to a serial of equivalent convex optimization problems. Then we develop a gradient-based resource allocation scheme to achieve the optimal solutions of the approximations. After a serial of approximations, the proposed scheme can finally converge to an optimal solution of the primal utility maximization model for resource allocation which satisfies the Karush–Kuhn–Tucker conditions.

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.

The main objective of this survey is to study the published articles to determine the most favorite data mining methods and gap of knowledge. Since the threat of pandemics has raised concerns for public health, data mining techniques were applied by researchers to reveal the hidden knowledge. Web of Science, Scopus, and PubMed databases were selected for systematic searches. Then, all of the retrieved articles were screened in the stepwise process according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist to select appropriate articles. All of the results were analyzed and summarized based on some classifications. Out of 335 citations were retrieved, 50 articles were determined as eligible articles through a scoping review. The review results showed that the most favorite DM belonged to Natural language processing (22%) and the most commonly proposed approach was revealing disease characteristics (22%). Regarding diseases, the most addressed disease was COVID-19. The studies show a predominance of applying supervised learning techniques (90%). Concerning healthcare scopes, we found that infectious disease (36%) to be the most frequent, closely followed by epidemiology discipline. The most common software used in the studies was SPSS (22%) and R (20%). The results revealed that some valuable researches conducted by employing the capabilities of knowledge discovery methods to understand the unknown dimensions of diseases in pandemics. But most researches will need in terms of treatment and disease control.

Background The PASCAL system is a novel device for edge-to-edge treatment of mitral regurgitation (MR). The aim of this study was to compare the safety and efficacy of the PASCAL to the MitraClip system in a highly selected group of patients with complex primary mitral regurgitation (PMR) defined as effective regurgitant orifice area (MR-EROA) ≥ 0.40 cm2, large flail gap (≥ 5 mm) or width (≥ 7 mm) or Barlow’s disease. Methods 38 patients with complex PMR undergoing mitral intervention using PASCAL (n = 22) or MitraClip (n = 16) were enrolled. Primary efficacy endpoints were procedural success and degree of residual MR at discharge. The rate of major adverse events (MAE) according to the Mitral Valve Academic Consortium (MVARC) criteria was chosen as the primary safety endpoint. Results Patient collectives did not differ relevantly regarding pertinent baseline parameters. Patients` median age was 83.0 [77.5–85.3] years (PASCAL) and 82.5 [76.5–86.5] years (MitraClip). MR-EROA at baseline was 0.70 [0.68–0.83] cm2 (PASCAL) and 0.70 [0.50–0.90] cm2 (MitraClip), respectively. 3D-echocardiographic morphometry of the mitral valve apparatus revealed no relevant differences between groups. Procedural success was achieved in 95.5% (PASCAL) and 87.5% (MitraClip), respectively. In 86.4% of the patients a residual MR grade ≤ 1 + was achieved with PASCAL whereas reduction to MR grade ≤ 1 + with MitraClip was achieved in 62.5%. Neither procedure time number of implanted devices, nor transmitral gradient differed significantly. No periprocedural MAE according to MVARC occured. Conclusion In this highly selected patient group with complex PMR both systems exhibited equal procedural safety. MitraClip and PASCAL reduced qualitative and semi-quantitative parameters of MR to an at least comparable extent. Graphic abstract

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.

The mission of theoretical cryptography is to define and construct provably secure cryptographic protocols and schemes. Without proofs of security, cryptographic constructs offer no guarantees whatsoever and no basis for evaluation and comparison. As most security proofs necessarily come in the form of a reduction between the security claim and an intractability assumption, such proofs are ultimately only as good as the assumptions they are based on. Thus, the complexity implications of every assumption we utilize should be of significant substance, and serve as the yard stick for the value of our proposals. Lately, the field of cryptography has seen a sharp increase in the number of new assumptions that are often complex to define and difficult to interpret. At times, these assumptions are hard to untangle from the constructions which utilize them. We believe that the lack of standards of what is accepted as a reasonable cryptographic assumption can be harmful to the credibility of our field. Therefore, there is a great need for measures according to which we classify and compare assumptions, as to which are safe and which are not. In this paper, we propose such a classification and review recently suggested assumptions in this light. This follows the footsteps of Naor Crypto 2003. Our governing principle is relying on hardness assumptions that are independent of the cryptographic constructions.

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.

The ScienceWISE system is a collaborative ontology editor and paper annotation tool designed to help researchers in their discovery. In this paper, we describe the system currently deployed at sciencewise.info and the exposition of its data as Linked Data. During the “RDFization” process, we faced issues to encode the knowledge base in SKOS and find resources to link to on the LOD. We discuss these issues and the remaining open challenges to implement some target features.

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.

Part 13: Environmental and Earth Applications of AI; International audience; Recycling has been gaining ground, thanks to the recent progress made in the related technology. However, a limiting factor to its wide adoption, is the lack of modern tools for managing the collection of recyclable resources. In this paper, we present EcoTruck, a management system for the collection of recyclable paper products. EcoTruck is modelled as a multi-agent system and its implementation employs Erlang, a distribution-oriented declarative language. The system aims to automate communication and cooperation of parties involved in the collection process, as well as optimise vehicle routing. The latter have the effect of minimising vehicle travel distances and subsequently lowering transportation costs. By speeding up the overall recycling process, the system could increase the service throughput, eventually introducing recycling methods to a larger audience.

This paper takes the management system of paper machine’s disassembly and assembly as research objects, and introduces RFID technology as well as the application of RFID. Then it establishes basic information management of paper machine, marking information management, installation information management, serial communication and other functional modules. The monitoring system adopts VC6.0 and SQL as the original developing tools. At first, it needs to analyse and construct system functional modules of paper machine, then it designs engineering framework-a kind of visual user management interface- in VC platform. Finally, it does the mapping coefficient and data transmitting from the engineering framework to database by ADO database access.

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.

This paper introduces the compelled certificate creation attack, in which government agencies may compel a certificate authority to issue false SSL certificates that can be used by intelligence agencies to covertly intercept and hijack individuals' secure Web-based communications.

Up to the twenty-first century, paper is still widely adopted for recording and reading. However, paper-based materials are fully capable of presenting abstract concepts and complicated knowledge with static text and figures. Learners usually need timely and adequate supports when encountering difficulties during learning. With a consideration of applying technologies, the learning tool must have a certain mobility and accessibility for acquiring facilitative resources. Using the networking capability of smartphone to access digital content from the Internet to enrich conventional paper-based learning activities is worth investigating. This chapter introduces an augmentation-enhanced learning context with an integration of digital content into paper-based materials in order to facilitate learning. Constructive feedback, scaffolding questioning, and procedural scaffolding are three strategies applied into the instructional designs and learning system. Quasi-experiments for personal learning and collaborative learning were also conducted to evaluate the effects on learning performance. The results suggest that the three instructional designs had significantly positive effects on individual’s learning performance. Team’s learning performance and team’s discourse levels were promoted as well. This chapter lays out a strong foundation for researchers to further explore how to better design different learning strategies for different learning subjects in the augmentation-enhanced learning context using smartphones. It is hoped that educational practitioners are able to obtain concrete ideas and solutions on how to better leverage the benefits of both paper-based content and digital learning materials in a real blended learning environment.

Almost everyone agrees on the central role that simulation plays in the understanding of complex systems such as the 3D network formed by stacking millions of fibers on top of each other in a paper sheet. Clearly, the computational implementation of the few models which describe the microstructure of paper is far from trivial. Unfortunately, to our knowledge, there is no description in the literature of the methodology used for programming these algorithms. As a contribution towards overcoming this gap, the present article explains the software implementation of key features of a 3D random fiber deposition model into a high-level MATLAB computer code.

An increasing number of Internet traders exclusively sell digital products. These digital products can include media files, licenses, services, or subscriptions. We consider the concept of digital provenance in reseller chains. The goal of this work is to provide an honest customer with a guarantee on the origin and ownership history for a digital item even when the reseller they are dealing with is untrusted. We introduce a protocol called the Tagged Transaction protocol which uses a third party called the Tag Generation Centre (TGC) to provide a method for honest customers to check they are purchasing a legitimate item, anonymity for customers and resellers, a method for customers to resell items they have purchased to other customers, and verification of the TGC.

International audience; This paper deals with the improvement of the Dirty Paper Trellis Code (DPTC) watermarking algorithm. This watermarking algorithm is known to be one of the best among the high rate watermarking schemes. Nevertheless, recent researches reveal its security weakness. Previously, we proposed to reinforce its security by using a secret space before the embedding. This secret space requires to compute projections onto secrets carriers. When dealing with high rate watermarking, the CPU cost for those projections is dramatically high. After introducing the watermarking scheme, we then propose two Space Division Multiplexing (SDM) approaches which reduce the complexity. Evaluations are achieved with four different attacks and show that our proposal gives better robustness results with SDM approaches.

With tactile paper prototyping user interfaces can be evaluated with blind users in an early design stage. First, we describe two existing paper prototyping methods, visual and haptic paper prototyping, and indicate their limitations for blind users. Subsequently, we present our experiences while preparing, conducting and analysing tests performed using tactile paper prototyping. Based on our experiences, we provide recommendations for this new usability evaluation method.

This paper presents an evaluation framework for analytical methods of integrating eWOM Information. This framework involves a communication model that assumes a set of human subjective probabilities called an belief source and includes two translation processes: (1) encoding the belief source into a representation to communicate with a computer; these encoded messages are called eWOM messages, and (2) in the computer, decoding the eWOM messages to estimate the probabilities in the belief source. The efficiency of reducing the difficulty of describing the belief source and the accuracy of reconstructing the belief source are quantitated using this model. The evaluation processes are illustrated with an analytical method of integrating eWOM messages for probabilistic classification problems.

According to the fuzziness of Each index in Test quality evaluation, The entropy value theory of information will be used to test quality evaluation, use The difficulty, degree of differentiate, believe degree, validity and the standard deviation. As the impact of the test quality evaluation index. Establish a comprehensive evaluation index system, Using the information entropy as evaluation index weight coefficient, which can effectively solve the weight distribution difficulties. Weight is an objectivity, This method is a new test quality evaluation method, and connecting with the example of application, The results show that the method was simple, practical and reliable.

In this world of digital and social media booms, a number of people spend their valuable times burying heads in smartphones, resulting in unintentional increased gaps in physical relationship with people nearby. A hybrid digital-physical medium is a possible solution for this problem by means of externalizing social media data and integrating them into a physical medium somehow. In this way, using social media will simultaneously connect us with both virtual and physical worlds.

The Linked Data effort has been focusing on how to publish open data sets on the Web, and it has had great results. However, mechanisms for updating linked data sources have been neglected in research. We propose a structure for Linked Data resources into named graphs, connected through hyperlinks and self described with light metadata, that is a natural match for using standard HTTP methods to implement application-specific (high-level) public update APIs.

This paper presents some algorithms for a novel simulation of the folding and cut crafts in Chinese Paper-cut. All algorithms in simulation are designed by consideration of the real Paper-cut's whole process. We applies area filling algorithm, polygon clipping algorithm, contour extraction algorithm and subdivision curve algorithm, with the proper improvement that meets the technique of the art in the nature, to yield some vivid Paper-cut works. Our approach is feasible to anyone with the desire, due to Paper-cut illumines itself in 2D and all the operations are also in 2D.Moverover, recent compelling graphic systems, such as Flash, Photoshop, Maya and 3DMax, did not provide a similar interface for paper's fold and decorative pattern which are primary elements in Paper-cut. However, our approach not only meets the interest of the Paper-cut, but also holds an interface for these compelling systems because of measuring up the SVG.

In Role Based Access Control (RBAC) systems, formulating a correct set of roles, assigning appropriate privileges to roles, and assigning roles to users are the fundamental design tasks. Whether these tasks are performed by a human (e.g., system administrator) or by a machine (e.g., expert system), misconfigurations are likely to occur. The misconfigurations could manifest as under-privileges (fewer privileges assigned) or over-privileges (more privileges than necessary). In this paper, we describe an approach based on role mining to detect and correct such misconfigurations. Here, the overlap among the users and privileges of different roles is used to identify possible misconfigurations.

HCI have long moved beyond the evaluation setting of a single user sitting in front of a single desktop computer, yet many of our fundamentally held viewpoints about evaluation continues to be ruled by outdated biases derived from this legacy. We need to engage with real users in 'Living Laboratories', in which researchers either adopt or create functioning systems that are used in real settings. These new experimental platforms will greatly enable researchers to conduct evaluations that span many users, places, time, location, and social factors in ways that are unimaginable before.

Recent studies in science and engineering education support that inductive learning activities encouraging active student involvement may improve students’ motivation, development of soft skills and academic performance, compared to traditional lectures. Until recently, several technology-enhanced learning environments have been proposed to facilitate such activities in classrooms. However, these commonly depend on dedicated hardware devices, such as clickers or tablet PCs. Contrastingly, smartphones are being massively adopted by society as these become increasingly powerful and inexpensive. Even so, the use of smartphones as learning tools in lecture halls has still not been widely adopted. In this paper we present CollPhoto, a paper-plus-smartphone environment that supports face-to-face problem solving activities in the classroom. CollPhoto provides the instructor with instant visibility of students’ work, and facilitates him/her conducting discussions, based on a selection of students’ responses. We report on the design and initial validation of CollPhoto in the context of two computer science courses.

BackgroundOptimal detection and surveillance of bladder cancer (BCa) rely primarily on the cystoscopic visualization of bladder lesions. AI-assisted cystoscopy may improve image recognition and accelerate data acquisition.ObjectiveTo provide a comprehensive review of machine learning (ML), deep learning (DL) and convolutional neural network (CNN) applications in cystoscopic image recognition.Evidence acquisitionA detailed search of original articles was performed using the PubMed-MEDLINE database to identify recent English literature relevant to ML, DL and CNN applications in cystoscopic image recognition.Evidence synthesisIn total, two articles and one conference abstract were identified addressing the application of AI methods in cystoscopic image recognition. These investigations showed accuracies exceeding 90% for tumor detection; however, future work is necessary to incorporate these methods into AI-aided cystoscopy and compared to other tumor visualization tools. Furthermore, we present results from the RaVeNNA-4pi consortium initiative which has extracted 4200 frames from 62 videos, analyzed them with the U-Net network and achieved an average dice score of 0.67. Improvements in its precision can be achieved by augmenting the video/frame database.ConclusionAI-aided cystoscopy has the potential to outperform urologists at recognizing and classifying bladder lesions. To ensure their real-life implementation, however, these algorithms require external validation to generalize their results across other data sets.

Geoinformation systems (GIS) contain information about objects in geographic space; the focus on geographic space [1] determines the scale of spatial objects and processes of interest at a spatial resolution of approximatively 0.1 m to 40.000 km and to changes occurring once a minute to once a million years. Geographic information is a diverse field which includes many special applications, each of which has special requirements, with special kinds of geometry and particular geometric operations.

Recently, a number of ID-based authenticated key agreement protocols from bilinear pairings have been proposed. In this paper we present security analysis of four ID-based authenticated key agreement protocols from pairings proposed in [11, 12, 7, 18]. These results demonstrate that no more ID-based authenticated key agreement protocols should be constructed with such ad-hoc methods, i.e, the formal design methodology as in [1, 2, 3, 10] should be employed in future design.

Cooperation between participants is essential to P2P applications' viability. Due to obscure possibility to match peers' needs and supplies in pairs, the widely used pair-wise exchange-based incentive schemes perform poorly. The N-way exchange-based incentive scheme enlarges the matching possibility by introducing n person exchanges. But some old problems remain and some new ones emerge with the N-way design. In this paper we present an enhanced n-way exchange-based incentive scheme for P2P file sharing systems. By distributing extra tasks to all the peers involved in an n-way exchange, the proposed scheme eliminates prohibitive computation and communication cost on the cooperators, resulting in greater efficiency, effectiveness, and security.

There has been considerable interest recently on developing a system to track items like pharmaceutical drugs or food products. Such a system can help prevent counterfeits, aid product recall, and improve general logistics. In this paper, we present such system based on radio frequency identity (RFID) technology. Our solution provides the means of storing the entire movement of the item from original manufacturer to final consumer on the RFID tag itself, and also makes it more difficult to introduce large numbers of counterfeits. The solution also allows the end user to easily verify the authenticity of the item.

A low-rate DoS attack to iterative servers has recently appeared as a new approach for defeating services using rates of traffic that could be adjusted to bypass security detection mechanisms. Although the fundamentals and effectiveness of these kind of attacks are known, it is not clear how to design the attack to achieve specific constraints based on the used rate and the efficiency in denial of service obtained. In this paper, a comprehensive mathematical framework that models the behaviour of the attack is presented. The main contribution of this model is to give a better understanding of the dynamics of these kind of attacks, in order to facilitate the development of detection and defense mechanisms.

Though computing environments are developed very rapidly, people use paper documents as ever. In this paper, we propose the Advanced Paper Document (APD), which expands the function of paper documents, based on the Augmented Desk system. To incorporate physical paper documents with digital documents in a projection display system without being required to use additional sensors, we use a gesture recognition method. The APD has advantages of paper and digital documents, and provides a user with a natural and intuitive environment. As shown by experimental results, the proposed the APD is applicable to provide an interactive computing environment.

We examine the properties and use of paper in everyday settings and discuss the motivation for retaining paper as an information medium. In particular, we consider the use of paper maps and guidebooks by tourists during city visits as an example of a mobile and collaborative environment. We then go on to present recent developments in technologies for digital paper and how they can be used to seamlessly integrate digital and printed information.

RC4 is (still) a very widely-used stream cipher. Previous work by AlFardan et al. (USENIX Security 2013) and Paterson et al. (FSE 2014) exploited the presence of biases in the RC4 keystreams to mount plaintext recovery attacks against TLS-RC4 and WPA/TKIP. We improve on the latter work by performing large-scale computations to obtain accurate estimates of the single-byte and double-byte distributions in the early portions of RC4 keystreams for the WPA/TKIP context and by then using these distributions in a novel variant of the previous plaintext recovery attacks. The distribution computations were conducted using the Amazon EC2 cloud computing infrastructure and involved the coordination of 213 hyper-threaded cores running in parallel over a period of several days. We report on our experiences of computing at this scale using commercial cloud services. We also study Microsoft’s Point-to-Point Encryption protocol and its use of RC4, showing that it is also vulnerable to our attack techniques.

Memory transactions provide programmers with a convenient abstraction for concurrent programs: a keyword such as atomic designating a region of code that appears, from the perspective of concurrent threads, to execute atomically. Unfortunately, existing implementations in the form of software transactional memory STM are often ineffective due to their monolithic nature: every single read or write access is automatically tracked and recorded. In this statement, we advocate a transactional model of programming without a heavyweight software transactional memory, and describe some related, open research challenges. We suggest that a model based on persistent data structures could permit a variety of transactional algorithms to coexist in a library of composable transactional objects. Applications are constructed by snapping these objects together to form atomic transactions, in much the same way that today's Java programmers compose their applications from libraries such as java.util.concurrent. We report preliminary results developing this library in ScalaSTM, and discuss the challenges ahead.

U-Prove is a credential system that allows users to disclose information about themselves in a minimalistic way. Roughly speaking, in the U-Prove system a user obtains certified cryptographic tokens containing a set of attributes and is able to disclose a subset of his attributes to a verifier, while hiding the undisclosed attributes. In U-prove the actual identity of a token holder is hidden from verifiers, however each token has a static public key (i.e. token pseudonym), which makes a single token traceable, by what we mean that, if a token is presented twice to a verifier, then the verifier knows that it is the same token. We propose an extension to the U-Prove system which enables users to show U-Prove tokens in a blinded form, so even if a single token is presented twice, a verifier is not able to tell whether it is the same token or two distinct tokens. Our proposition is an optional extension, not changing the core of the U-Prove system. A verifier decides whether to use issuer signatures from U-Prove, or the blind certificates from the extension.