Reviewerly/exHarmony huggingface dataset:
Control Flow and Pointer Integrity Enforcement in a Secure Tagged Architecture

Control flow attacks exploit software vulnerabilities to divert the flow of control into unintended paths to ultimately execute attack code. This paper explores the use of instruction and data tagging as a general means of thwarting such control flow attacks, including attacks that rely on violating pointer integrity. Using specific types of narrow-width data tags along with narrow-width instruction tags embedded within the binary facilitates the security policies required to protect against such attacks, leading to a practically viable solution. Co-locating instruction tags close to their corresponding instructions within cache lines eliminates the need for separate mechanisms for instruction tag accesses. Information gleaned from the analysis phase of a compiler is augmented and used to generate the instruction and data tags. A full-stack implementation that consists of a modified LLVM compiler, modified Linux OS support for tags and a FPGA-implemented CPU hardware prototype for enforcing CFI, data pointer and code pointer integrity is demonstrated. With a modest hardware enhancement, the execution time of benchmark applications on the prototype system is shown to be limited to low, single-digit percentages of a baseline system without tagging.
FIDO2, CTAP 2.1, and WebAuthn 2: Provable Security and Post-Quantum Instantiation

The FIDO2 protocol is a globally used standard for passwordless authentication, building on an alliance between major players in the online authentication space. While already widely deployed, the standard is still under active development. Since version 2.1 of its CTAP sub-protocol, FIDO2 can potentially be instantiated with post-quantum secure primitives.We provide the first formal security analysis of FIDO2 with the CTAP 2.1 and WebAuthn 2 sub-protocols. Our security models build on work by Barbosa et al. for their analysis of FIDO2 with CTAP 2.0 and WebAuthn 1, which we extend in several ways. First, we provide a more fine-grained security model that allows us to prove more relevant protocol properties, such as guarantees about token binding agreement, the None attestation mode, and user verification. Second, we can prove post-quantum security for FIDO2 under certain conditions and minor protocol extensions. Finally, we show that for some threat models, the downgrade resilience of FIDO2 can be improved, and show how to achieve this with a simple modification.
It’s like flossing your teeth: On the Importance and Challenges of Reproducible Builds for Software Supply Chain Security

The 2020 Solarwinds attack was a tipping point that caused a heightened awareness about the security of the software supply chain and in particular the large amount of trust placed in build systems. Reproducible Builds (R-Bs) provide a strong foundation to build defenses for arbitrary attacks against build systems by ensuring that given the same source code, build environment, and build instructions, bitwise-identical artifacts are created. Unfortunately, much of the software industry believes R-Bs are too far out of reach for most projects. The goal of this paper is to help identify a path for R-Bs to become a commonplace property.To this end, we conducted a series of 24 semi-structured expert interviews with participants from the Reproducible-Builds.org project, finding that self-effective work by highly motivated developers and collaborative communication with upstream projects are key contributors to R-Bs. We identified a range of motivations that can encourage open source developers to strive for R-Bs, including indicators of quality, security benefits, and more efficient caching of artifacts. We also identify experiences that help and hinder adoption, which often revolves around communication with upstream projects. We conclude with recommendations on how to better integrate R-Bs with the efforts of the open source and free software community.
HasChor: Functional Choreographic Programming for All (Functional Pearl)

Choreographic programming is an emerging paradigm for programming distributed systems. In choreographic programming, the programmer describes the behavior of the entire system as a single, unified program -- a choreography -- which is then compiled to individual programs that run on each node, via a compilation step called endpoint projection. We present a new model for functional choreographic programming where choreographies are expressed as computations in a monad. Our model supports cutting-edge choreographic programming features that enable modularity and code reuse: in particular, it supports higher-order choreographies, in which a choreography may be passed as an argument to another choreography, and location-polymorphic choreographies, in which a choreography can abstract over nodes. Our model is implemented in a Haskell library, HasChor , which lets programmers write choreographic programs while using the rich Haskell ecosystem at no cost, bringing choreographic programming within reach of everyday Haskellers. Moreover, thanks to Haskell's abstractions, the implementation of the HasChor library itself is concise and understandable, boiling down endpoint projection to its short and simple essence.
CHIP2022 Shared Task Overview: Medical Causal Entity Relationship Extraction

Modern medicine emphasizes interpretability and requires doctors to give reasonable, well-founded and convincing diagnostic results when diagnosing patients. Therefore, there are a large number of causal correlations in medical concepts such as symptoms, diagnosis and treatment in the text of the results of the inquiry. Explanation of relationships, and mining these relationships from text is of great help in improving the accuracy and interpretability of medical search results. Based on this, this paper constructs a new medical causality extraction dataset CMedCausal (Chinese Medical Causal dataset) and it is used in the CHIP2022 shared task, which defines three key types of medical causal relationships: causal relationship, conditional relationship, and hypothetical relationship. It consists of 9,153 medical texts with a total of 79,244 entity relationships annotated. Participants need to correctly label these correct reasoning relationships and corresponding subject-object entities. A total of 49 teams submitted results for the preliminary round with the highest Macro-F1 value of 0.4510. A total of 25 teams submitted results for final round with the highest Macro-F1 value of 0.4416.
When reality backfires: Product evaluation context and the effectiveness of augmented reality in e‐commerce

Abstract Augmented reality (AR) enables consumers to project product holograms into their surrounding real‐world context in real time using their mobile devices. Although AR may improve online consumers' product evaluation, AR‐deploying retailers give up control over the context in which their products are evaluated. As a result, AR retailers' products might end up being evaluated in unfavorable contexts, such as disorganized rooms. Negative spillover effects from such unfavorable AR contexts onto the perceptions of evaluated products may lead consumers to refrain from purchasing the products. In two online experiments and a controlled field study with a total of 1000 participants, we find that unfavorable AR contexts negatively affect consumers' product‐related purchase intention. This relationship is serially mediated by processing disfluency and deteriorating product quality perceptions of consumers. The negative contextual effects are mitigated if the product under evaluation is of unique design and thus more conceptually fluent or if the AR context becomes less perceptually salient and thus the product more perceptually fluent. We discuss diminished reality and facilitated product comparisons via AR as potential countermeasures for AR retailers and provide suggestions for future research.
Digital transformation and sustainable development in higher education in a post-pandemic world

ABSTRACTABSTRACTDigital technologies are now part of our daily lives, and the speed of their implementation and use has been accelerated as a result of the COVID-19 pandemic. Digital transformation, seen in the past as a problem, is now perceived as an important component in the future of sustainable development (SD), especially at higher education institutions whose operations have been adversely affected by the pandemic in many ways. The purpose of this paper is to analyse the subject matter of digital transformation and how it relates to a SD context. It reports on the results of a worldwide survey at higher education institutions, which identified some areas where the pandemic impacted and/or influenced their activities. The survey received 158 responses and a principal component analysis was performed to model the items associated with digital tools boosting SD, innovative business opportunities and ideas, and needs for improvement at HEIs. The results indicate that most part of the respondents developed digital skills and increased their involvement with e-learning and distance learning; however, more digital training is needed. Findings also support the role played by digital technologies in boosting SD at HEIs, and the role of institutions in promoting innovation through digital tools. Apart from an analysis of the extent to which the COVID-19 pandemic has contributed to digital transformation in an SD context in higher education institutions, the paper provides an assessment of trends and recommendations that may guide future developments in a post-pandemic work.KEYWORDS: Sustainable developmentsustainable development goalsdigital transformationhigher educationCOVID-19 pandemic AcknowledgmentsThis paper is part of the "100 papers to accelerate the implementation of the UN Sustainable Development Goals" initiative.Disclosure statementNo potential conflict of interest was reported by the authors.Anonymous treatment of respondents and ethical statementThe full questionnaire was designed to collect general information and ensure that details were anonymous. According to the German law, the study is exempted from ethical approval.Correction StatementThis article has been corrected with minor changes. These changes do not impact the academic content of the article.
Deep Learning and Vision Transformer for Medical Image Analysis

Artificial intelligence (AI) refers to the field of computer science theory and technology [...].
Virtual Influencers versus Real Influencers Advertising in the Metaverse, Understanding the Perceptions, and Interactions with Users

AbstractInfluencer marketing is developing at a fast pace. The metaverse offers new possibilities for brands to initiate influencer marketing. This study employs a qualitative approach. In total, 148 millennials were interviewed on their perceptions, involvement, and interactions with advertising and influencers in the metaverse. The study asked these participants to enter the metaverse; they were then asked questions. The first aim is to comprehend how participants react to advertising in the metaverse. The study differentiates between active participants and those who never entered the metaverse. The second aim is to comprehend whether virtual influencers can yield influence in the metaverse and how they are different from real influencers. Virtual influencers are virtual social robots that represent brands and engage in online sales experiences and/or advertising, and they often perform these tasks on social media platforms. Real influencers are human individuals who develop a large following and are capable of communicating directly with their audience. They often post about their own life experiences, product recommendations, and more. This research broadens the perspective on the metaverse as an influencer advertising medium. Notes1 McKinsey & Company (2022). Marketing in the metaverse: An opportunity for innovation and experimentation. Accessed on 5 Sept. 2022. https://www.mckinsey.com/business-functions/growth-marketing-and-sales/our-insights/marketing-in-the-metaverse-an-opportunity-for-innovation-and-experimentation.2 The Verge. Adidas sold more than $22 million in NFTs, but it hit a few snags along the way.https://www.theverge.com/2021/12/17/22843104/adidas-nfts-metaverse-sold-bored-ape.
zk-creds: Flexible Anonymous Credentials from zkSNARKs and Existing Identity Infrastructure

Frequently, users on the web need to show that they are, for example, not a robot, old enough to access an age restricted video, or eligible to download an ebook from their local public library without being tracked. Anonymous credentials were developed to address these concerns. However, existing schemes do not handle the realities of deployment or the complexities of real-world identity. Instead, they implicitly make assumptions such as there being an issuing authority for anonymous credentials that, for real applications, requires the local department of motor vehicles to issue sophisticated cryptographic tokens to show users are over 18. In reality, there are multiple trust sources for a given identity attribute, their credentials have distinctively different formats, and many, if not all, issuers are unwilling to adopt new protocols.We present and build zk-creds, a protocol that uses general-purpose zero-knowledge proofs to 1) remove the need for credential issuers to hold signing keys: credentials can be issued to a bulletin board instantiated as a transparency log, Byzantine system, or even a blockchain; 2) convert existing identity documents into anonymous credentials without modifying documents or coordinating with their issuing authority; 3) allow for flexible, composable, and complex identity statements over multiple credentials. Concretely, identity assertions using zk-creds take less than 150ms in a real-world scenario of using a passport to anonymously access age-restricted videos.
Scalable and Privacy-Preserving Federated Principal Component Analysis

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confidentiality. Our solution, SF-PCA, is an end-to-end secure system that preserves the confidentiality of both the original data and all intermediate results in a passive-adversary model with up to all-but-one colluding parties. SF-PCA jointly leverages multiparty homomorphic encryption, interactive protocols, and edge computing to efficiently interleave computations on local cleartext data with operations on collectively encrypted data. SF-PCA obtains results as accurate as non-secure centralized solutions, independently of the data distribution among the parties. It scales linearly or better with the dataset dimensions and with the number of data providers. SF-PCA is more precise than existing approaches that approximate the solution by combining local analysis results, and between 3x and 250x faster than privacy-preserving alternatives based solely on secure multiparty computation or homomorphic encryption. Our work demonstrates the practical applicability of secure and federated PCA on private distributed datasets.
Immersive experiences as a resource for promoting museum tourism in the Z and millennials generations

In recent years, immersive experiences have gained a leading role in cultural and museum tourism. However, not all the benefits of virtual reality as a promotional tool for museum tourism, especially among the younger generation, are being exploited. This paper conducted an experiment in three different immersive scenarios, using the virtual reality headset, the mobile application plus virtual reality glasses and video on a computer screen. The sample contained 157 young people from Gen Z and Millennials. The results have shown that, with higher experience immersion levels, there are higher levels of affective and conative performance in young people. In addition, where there are higher levels of immersive experience, young people with an active cultural profile have an increased affective and conative performance. Likewise, these young people are more proactive with the intention of an actual visit to the museum.
Augmented Reality and Virtual Reality

Recent technological advances have revolutionized the learning and teaching process. The integration of a particular technology will give limitless opportunities to obtain experiences that would not be otherwise available. Augmented reality (AR) and virtual reality (VR) are becoming more and more popular in education; therefore, educators and academics became interested in investigating their potential as learning environments for many disciplines including language learning. The purpose of this chapter is to discuss different applications of AR and VR in education and language learning. In order to fulfill this aim, different AR and VR technologies and their features were discussed. Furthermore, the affordances and challenges of AR and VR in language teaching and learning were pointed out. This chapter concludes with future directions for research regarding AR and VR in educational settings. The study includes some implications for practitioners and researchers interested in educational technologies.
EFL Teachers’ Perspectives toward the Use of ChatGPT in Writing Classes: A Case Study at Van Lang University

The introduction of ChatGPT is seen as a potential chance to improve second language learning and instruction. However, the acceptance of technology in education is dependent on instructors' views. As a consequence, it is vital to explore how EFL teachers assess the implementation of ChatGPT in language classes, particularly in Vietnam, where research on this topic is scarce. The goal of this study is to learn about EFL teachers' thoughts on using ChatGPT in writing sessions and to gather ideas for its implementation. The research involved twenty Van Lang University EFL teachers who utilized ChatGPT in their language education and taught numerous writing courses. An online survey and a structured interview were used to collect quantitative and qualitative data. The study's results show that EFL instructors at Van Lang University are enthusiastic about using ChatGPT in writing lessons. Furthermore, the research emphasizes the necessity of professional training for instructors, boosting user knowledge of the limits and possible hazards connected with ChatGPT, and assuring correct chatbot use as critical elements that contribute to its successful deployment.
Exploring nonlinear dynamics and network structures in Kuramoto systems using machine learning approaches

Recent advances in machine learning (ML) have facilitated its application to a wide range of systems, from complex to quantum. Reservoir computing algorithms have proven particularly effective for studying nonlinear dynamical systems that exhibit collective behaviors, such as synchronizations and chaotic phenomena, some of which still remain unclear. Here, we apply ML approaches to the Kuramoto model to address several intriguing problems, including identifying the transition point and criticality of a hybrid synchronization transition, predicting future chaotic behaviors, and understanding network structures from chaotic patterns. Our proposed method also has further implications, such as inferring the structure of neural networks from electroencephalogram signals. This study, finally, highlights the potential of ML approaches for advancing our understanding of complex systems.
MLAE2: Metareasoning for Latency-Aware Energy-Efficient Autonomous Nano-Drones

Safety, low-cost, small size, and Artificial Intelli-gence (AI) capabilities of drones have led to the proliferation of autonomous tiny Unmanned Aerial Vehicles (UAVs) in many applications which are dangerous, unknown, or time-consuming for humans. Deep Neural Networks (DNNs) have enabled au-tonomous navigation while using captured data by drone sensors as input to the model. Due to the extreme complexity of DNNs, cloud-based approaches have been highly addressed in which a drone is connected to the cloud and sends the data to the cloud, and takes the result. On the other hand, emerging tiny machine learning models and edge computing brings significant improvement in energy efficiency and latency with respect to cloud-based approaches. However, there is a trade-off in these two implementations for model accuracy, latency, and energy efficiency. For instance, applying tiny machine learning models leads to lower latency but it sacrifices model accuracy in comparison to cloud-based computing. To address these challenges, we consider multiple models and introduce a new approach named MLAE2 which applies Metareasoning approach for Latency-Aware Energy-Efficient autonomous drones. Metareasoning mon-itors parameters such as latency and energy consumption for different algorithms and chooses the appropriate algorithm due to the environmental situation changes. To Evaluate our approach we extract the power consumption and latency for both cloud-based computing and edge computing while deploying multiple models on a tiny drone named Crazyflie. The experimental results show that MLAE2 successfully meets the latency constraint while maximizing model accuracy and improving energy efficiency.
Spectre Declassified: Reading from the Right Place at the Wrong Time

Practical information-flow programming languages commonly allow controlled leakage via a declassify construct—programmers can use this construct to declare intentional leakage. For instance, cryptographic signatures and ciphertexts, which are computed from private keys, are viewed as secret by information-flow analyses. Cryptographic libraries can use declassify to make this data public, as it is no longer sensitive.In this paper, we study the interaction between speculative execution and declassification. We show that speculative execution leads to unintended leakage from declassification sites. Concretely, we present a PoC that recovers keys from AES implementations. Our PoC is an instance of a Spectre attack, and remains effective even when programs are compiled with speculative load hardening (SLH), a widespread compiler-based countermeasure against Spectre. We develop formal countermeasures against these attacks, including a significant improvement to SLH we term selective speculative load hardening (selSLH). These countermeasures soundly enforce relative non-interference (RNI): Informally, the speculative leakage of a protected program is limited to the existing sequential leakage of the original program. We implement our simplest countermeasure in the FaCT language and compiler—which is designed specifically for high-assurance cryptography—and we see performance overheads of at most 10%. Finally, although we do not directly implement selSLH, our preliminary evaluation suggests a significant reduction in performance cost for cryptographic functions as compared to traditional SLH.