bluuebunny/crossref_metadata_2025 huggingface dataset:
The importance of the nutritionist in the prevention and treatment of chronic non-communicable diseases
Authors: Chaves Tayssa Silva , da Silva Adryele Jesus
Published: July 2024

The study in question sought to highlight the importance of nutritional monitoring performed by the professional nutritionist in the prevention and treatment of Chronic Non-Communicable Diseases (NCDs). As well as reflecting on the importance of diet in the preventive care of NCDs and in their treatment, it shows the risk factors of the diseases and discusses how they can be avoided with nutritional monitoring, as well as points out some functional foods that have been found to be beneficial in the fight against these diseases. The research method of this article was a literature review, and full articles were searched to foster the study, laws, resolutions and quantitative and qualitative data to support the article. It can be concluded from the research carried out in this article that the nutritionist is the qualified and indicated professional to prevent and treat NCDs, and their performance in society can reduce health expenses, as well as reduce the prevalence of diseases by adopting diet therapy as prevention and treatment of chronic non-communicable diseases.
The effects of floods on mental health and the incidence of diseases
Authors: Lourenço Ricardo do Vale , Teixeira Aldira Samantha Garrido , Rodrigues Evellyn da Silva , Daudt Fabiani Warol
Published: July 2024

Floods and floods represent natural disasters that occur frequently and bring devastation, profoundly affecting the health of affected communities. It is vital to understand how these events impact both physical health, especially about communicable diseases, and mental health, including problems such as depression and anxiety, as well as other psychosocial aspects. This theoretical study was based on a broad literature review carried out between January and June, analyzing publications on hydrological phenomena and enriched with casestudies from various regions of Brazil. The discussion also explored how public policies and cooperation between different sectors can be essential strategies for reducing the damage from these disasters and managing related risks.
Miscarriage of justice: State reparation and criminal review
Authors: Goulart Loreano José de Jesus
Published: July 2024

Miscarriage of justice is a factor present in the judicial system, affecting the lives of countless people, who suffer directly from their conviction or indirectly from its repercussions. This paper aims to present a study on miscarriage of justice, especially focusing on errors resulting from criminal proceedings, seeking to demonstrate the State's responsibility to make reparations for errors in the provision of criminal justice. Using an interdisciplinary study of various areas of law and specific cases, the paper seeks to delve deeper into the reasons that may be determining factors in the erroneous outcome of the process. The paper is based on data research that allows for a deeper understanding of the problem, as well as on the analysis of the historical case of the Naves brothers and other cases of error. It also presents the Innocence Project program, from the USA and now in Brazil, whose role is to investigate and file review actions in cases where there was an error in the judgment of the criminal action. This research also delves deeper into the autonomous action of criminal review, which presents itself as one of the tools to repair the error and provide due compensation. The use of mechanisms such as adversarial proceedings are ways of reducing errors in actions; furthermore, the possibility of the procedural and constitutional system providing for reparation and compensation is a positive factor, and its application should be favorable to the detriment of res judicata.
Quality of guanandi wood (Calophyllum brasiliense Camb.) after heat treatment
Authors: Barreiros Ricardo Marques , de Souza Júnior Walter , Dias Kelly Bossardi
Published: July 2024

The scarcity of native forests and the national code that protects them have made it difficult to obtain timber considered as a good quality, thus making it necessary to discover new species or practices that make reforestation timber an alternative to reduce pressure on native forests. The objective of this study was to analyze the behavior of Guanandi wood ( Calophyllum brasiliense Camb.) regarding its physical properties when subjected to heat treatment and compare it to natural wood. In this work, boards were obtained from the basal logs of five 13-year-old trees, which were subjected to high temperatures, namely 140, 160, 180, 200 and 220°C, and their physical properties were analyzed, such as basic specific gravity, apparent specific gravity at 12% humidity, loss of mass of the heat treatment boards, swelling, as well as the presence of warping and surface and/or end cracks. The results showed that mass loss, basic density and anisotropy coefficient increased with increasing temperature, even in relation to natural wood. Density at 12% and linear and volumetric dimensions decreased with increasing temperature, even in relation to natural wood. Temperatures of 180, 200 and 220°C generally caused defects such as cracks in the direction of the pith and cupping, which were not present at lower temperatures or in the control.
Revolutionizing Tomorrow: The Role of Artificial Intelligence in the Accounting Profession
Authors: Vandapuye Sophia , Jabraoui Siham
Published: July 2024

Given the increasingly sophisticated technological advancements that are reshaping our current work environment, it is crucial to acknowledge that the concept of artificial intelligence represents a fundamental lever in the development process of the accounting profession, which accountants must integrate. This profession is undergoing significant transformation, as tasks once thought to be exclusive to humans are now being performed by machines. By incorporating artificial intelligence, the accounting profession would experience an evolution through the involvement of robots and machines within their firms, simplifying many tasks and enabling professionals to focus on high-value-added activities. Accountants are developing professional profiles through complex systems based on artificial intelligence, aiming to enhance the skills and performance of their employees while remaining competitive. To achieve this, employees must be ready to adapt and acquire training to effectively embrace and navigate this digital revolution.
In line with this objective, this research paper aims to analyze the implication of integrating artificial intelligence on the accounting profession. To accomplish this, the study relies primarily on existing theories and includes a qualitative investigation through semi-structured interviews conducted with 20 accounting firms operating in different cities across Morocco
Legal Entity Status of Individual Companies Which no Longer Meet the Criteria for Micro and Small Enterprises
Authors: Prasistanti Aninda Rehani , Sihabudin Sihabudin , Laila Fathul
Published: July 2024

An individual company is obliged to modify its legal status to a Capital Partnership Company if it is considered as no longer applies for Micro and Small Enterprises (UMK) / MSEs criteria. However, there are no provisions regarding the consequences if it is not made. It leads to unclear legal entity status and the responsibilities of individual companies which do not meet the standards of the Micro and Small Enterprises (UMK). This study aims to (1) analyze Individual Companies legal entity status which does not apply the UMK standards, and (2) analyze the legal implications of Individual Companies which no longer meet the UMK criteria. This study used normative juridical research method with a statutory approach and analysis of legal concepts. The results show that individual legal entity status of companies which do not meet the UMK criteria has not been rigidly regulated in the Job Creation Law or its regulations. However, individual companies which do not meet the UMK criteria are considered as no longer meet the legal entity requirements which are regulated in the Job Creation Law. Therefore, de jure, Individual Company legal entity status is no longer a legal entity, but de facto it is still registered as a legal entity. In addition, the legal implication is considered as the loss of the limited liability of the Individual Company.
El primer auge de la industria de producción cinematográfica en México (1929-1936): una contribución a la historia económica del cine
Authors: Galván Gómez Carlos Alejandro
Published: July 2024

Por medio de un análisis con perspectiva empresarial, el presente artículo analiza el auge que expe­rimentó la industria de producción cinematográfica mexicana a inicios de la década de 1930. Se propone que el auge debe ser entendido dentro del contexto de la transición internacional al cine sonoro y de efervescencia nacionalista en México. Del mismo modo, se propone que el auge fue resultado del aprovechamiento de dichos contextos por parte de la Compañía Nacional Productora de Películas, así como el entusiasmo generado por su cinta fundacional, Santa (Moreno, 1932). Los estudios sobre la industria cinematográfica mexicana han enfati­zado el papel de los elementos estéticos y sociales para entender el desarrollo del cine mexicano, sin embargo, el presente estudio busca contribuir a esta historiografía incorporando elementos microeconómicos, así como herramientas de análisis de la literatura sobre formación de industrias.
Auge, limitaciones y transformación del proceso industrial mexicano: 1940-2000
Authors: Fujigaki Cruz Esperanza , Escamilla Trejo Adrián
Published: July 2024

Este trabajo tiene como propósito analizar algunas de las características principales de la etapa del proceso industrial mexicano que transcurre de 1940 a finales del siglo XX. La intención es mostrar las tenden­cias generales, los alcances, límites y contradicciones que acompañaron el periodo de mayor desarrollo industrial de México, así como las particularidades relevantes de su desenvolvimiento y transformación a lo largo de estas décadas, aquellos aspectos que lo impulsaban y otros que lo frenaban. Para alcanzar estos objetivos se recurre a una revisión historiográfica, donde se examinan tanto autores de la etapa estudiada, como otros de la actuali­dad; asimismo, se realiza un breve análisis hemerográfico y estadístico, que muestra esas directrices y señala parte de su problemática.
“Los precios que tiene China son como los del INDEC de Moreno”
Authors: Ceballos Rocío
Published: July 2024

En este trabajo analizamos el modo en que la Unión Industrial Argentina (UIA) construyó su po­sicionamiento político contra al reconocimiento de China como economía de mercado durante la gestión de Cambiemos. También identificamos las fuentes de poder instrumental que los empresarios, nucleados en dicha cámara, desplegaron para incidir sobre el posicionamiento del Poder Ejecutivo Nacional. Para esto nos con­centramos en la dimensión político-institucional de la acción empresarial organizada y realizamos un análisis cualitativo a partir del relevamiento de fuentes periodísticas, documentos corporativos y bibliografía especiali­zada en el tema durante el período 2015-2017. Este caso de estudio nos muestra que las elites económicas no necesariamente detentan un poder omnímodo sobre el Estado –al menos no de la misma forma y en los mismos ámbitos a lo largo del tiempo– dado que los industriales no pudieron negociar con el gobierno la apertura co­mercial controlada.
Desarrollo e institucionalidad de las telecomunicaciones satelitales en Argentina
Authors: Pascuini Paulo Daniel , Alvarez Valentín
Published: July 2024

A partir del desarrollo de la industria satelital argentina, emergieron nuevos actores asociados al sector de telecomunicaciones y se diseñaron las reglas de juego que aún hoy regulan su actividad. Este trabajo analiza cómo el marco institucional vigente afecta las posibilidades para aprovechar recursos y oportunidades que promuevan el sector de telecomunicaciones satelitales a la luz de la evolución en: el rol del operador de bandera; la gestión de posiciones orbitales geoestacionarias ante la Unión Internacional de Telecomunicaciones y la puesta en servicio de satélites en estas posiciones; y la regulación de la provisión local de servicios satelitales. El estudio encuentra áreas para mejorar el aprovechamiento de recursos y oportunidades en el sector, redise­ñando instituciones que fortalezcan la coordinación entre entidades de gobierno y la gestión del trade-off com­petencia-protección.
Entre rieles llegó la modernidad: El ferrocarril en Yucatán durante el Porfiriato (1876-1911)
Authors: García Tinajero Violeta
Published: July 2024

Este artículo estudia la política económica que se implementó en la construcción del ferrocarril yucateco durante el Porfiriato (1876-1910), a partir del análisis de los discursos de la élite económica y política inmersa en el proceso de construcción y administración de las vías férreas en Yucatán. Se inserta en un contexto internacional donde México se incorpora al mercado mundial como una economía primario-exportadora de acuerdo con los requerimientos de Estados Unidos e Inglaterra. En lo que respecta a Yucatán, fue el principal productor de henequén a nivel global, principalmente para el mercado norteamericano. Ante la creciente de­manda internacional del henequén era necesaria una red ferroviaria que conectara las haciendas con el puerto de exportación, por esta razón, la élite local, dueña de las haciendas henequeneras, llevó a cabo la construcción de los ferrocarriles con el apoyo del capital extranjero.
Historia de la industria en México, siglos XIX y XX
Authors: Odisio Juan , Quintanar Zárate Iliana Marcela
Published: July 2024

Presentacion del dossier sobre historia de la industria en Mexico durante los siglo XIX y XX.
Un acercamiento al desempeño de la industria cervecera durante la recesión y la crisis económica de 1926-1932
Authors: López López Adriana , Romero Sotelo María Eugenia
Published: July 2024

La historiografía sobre la recesión de 1926 y la crisis de 1929 en México no ha prestado suficiente atención a la forma en la que afectó a los sectores ligados al mercado interno. Este trabajo es un acercamiento al desempeño económico de la industria cervecera entre 1926 y 1932, que fueron los años en los que ocurrieron estos fenómenos. Se señalan los factores que determinaron su crecimiento y la manera en la que fue afectada por la recesión que inició en 1926 y por la crisis internacional de 1929.
Aldo Ferrer y su contribución al desarrollo económico de América Latina: sus principales aportes en el pensamiento latinoamericano
Authors: Ibañez Diosquez Nattia
Published: July 2024

El presente trabajo propone una relectura de las principales ideas del economista argentino, Aldo Ferrer, con relación al desarrollo económico de América Latina. Ferrer es considerado uno de los principales referentes del estructuralismo latinoamericano -formado en la matriz de análisis promovida por Raúl Prebisch, y cuyo pensamiento fue evolucionando a lo largo de su extensa carrera académica y, su acotada participación política.
Este trabajo efectúa un breve recorrido por la información biográfica de Ferrer, destacando sus obras más relevantes y sus aportes al pensamiento económico latinoamericano. Se enfatiza en las ideas que propuso Ferrer para promover el desarrollo latinoamericano y, especialmente, argentino. Por otra parte, se contrastan algunas de esas ideas con las políticas implementadas en Argentina, en las primeras dos décadas del siglo en curso.
De ese modo, el estudio busca incentivar la reflexión sobre la vigencia del pensamiento de Ferrer, en una coyuntura en la cual la búsqueda de políticas para promover el desarrollo es una necesidad crítica en la región latinoamericana. Además, se considera que sus contribuciones para el pensamiento económico de esta región pueden y deberían servir para la planificación de políticas de desarrollo, en los países de América Latina, en el siglo veintiuno.
Economia criativa: a relevância da indústria cultural para o progresso econômico da Coreia do Sul
Authors: Alencar Billig Osvaldo , Costa Silva Erica Larissa
Published: July 2024

Esta pesquisa tem como objetivo entender a relevância da Indústria Cultural como instrumento da Economia Criativa na Coreia do Sul. Foi proposto discutir a literatura sobre Economia Criativa e Indústria Cultural, como também identificar os fatores que impulsionaram esse setor na Coreia do Sul e por fim analisar os efeitos experienciados pelo país. A metodologia utilizada foi a pesquisa bibliográfica por meio de livros, revistas internacionais, teses e artigos científicos.
Imperialismo, capital y guerra, en el siglo XXI
Authors: Berdú Guilherme Paul
Published: July 2024

La globalización de finales del siglo XX no marca el fin del imperialismo, por el contrario, representa un salto cualitativo en el mismo. Así se forma la tríada imperialismo, capital y guerra, redefiniendo funciones y tácticas de intervención en la economía, en la vida social y política. El objetivo de este artículo es proponer un debate teórico a cerca de esos conceptos y su vinculación. Esperamos contribuir a elucidar las diferentes formas que adopta el imperialismo, en el siglo XXI.
Divisible E-Cash for Billing in Private Ad Retargeting
Authors: Liao Kevin , Corrigan-Gibbs Henry , Boneh Dan
Published: July 2024

This paper presents new techniques for private billing in systems for privacy-preserving online advertising. In particular, we show how an ad exchange can use an e-cash scheme to bill advertisers for ad impressions without learning which client saw which ad: The exchange issues electronic coins to advertisers, advertisers pay publishers (via clients) for ad impressions, and publishers unlinkably redeem coins with the exchange. To implement this proposal, we design a new divisible e-cash scheme that uses modern zero-knowledge proofs to reduce the ad exchange's computational costs by roughly 250x compared to the previous state-of-the-art. With our new e-cash scheme, our private-billing infrastructure adds little overhead to existing private ad-retargeting systems: less than 63 ms of latency, negligible client computation, less than 3.2 KB of client communication, and a combined server operating cost (advertisers, publishers, and exchange) of less than 1% of ad spend, an over 5x savings compared to the previous state-of-the-art.
Fantômas: Understanding Face Anonymization Reversibility
Authors: Todt Julian , Hanisch Simon , Strufe Thorsten
Published: July 2024

Face images are a rich source of information that can be used to identify individuals and infer private information about them. To mitigate this privacy risk, anonymizations employ transformations on clear images to obfuscate sensitive information, all while retaining some utility. Albeit published with impressive claims, they sometimes are not evaluated with convincing methodology.
Reversing anonymized images to resemble their real input --- and even be identified by face recognition approaches --- represents the strongest indicator for flawed anonymization. Some recent results indeed indicate that this is possible for some approaches. It is, however, not well understood, which approaches are reversible, and why. In this paper, we provide an exhaustive investigation in the phenomenon of face anonymization reversibility. Among other things, we find that 11 out of 15 tested face anonymizations are at least partially reversible and highlight how both reconstruction and inversion are the underlying processes that make reversal possible.
Automatic Generation of Web Censorship Probe Lists
Authors: Tang Jenny , Alvarez Léo , Brar Arjun , Hoang Nguyen Phong , Christin Nicolas
Published: July 2024

Domain probe lists---used to determine which URLs to probe for Web censorship---play a critical role in Internet censorship measurement studies. Indeed, the size and accuracy of the domain probe list limits the set of censored pages that can be detected; inaccurate lists can lead to an incomplete view of the censorship landscape or biased results. Previous efforts to generate domain probe lists have been mostly manual or crowdsourced. This approach is time-consuming, prone to errors, and does not scale well to the ever-changing censorship landscape. In this paper, we explore methods for automatically generating probe lists that are both comprehensive and up-to-date for Web censorship measurement. We start from an initial set of 139,957 unique URLs from various existing test lists consisting of pages from a variety of languages to generate new candidate pages. By analyzing content from these URLs (i.e., performing topic and keyword extraction), expanding these topics, and using them as a feed to search engines, our method produces 119,255 new URLs across 35,147 domains. We then test the new candidate pages by attempting to access each URL from servers in eleven different global locations over a span of four months to check for their connectivity and potential signs of censorship. Our measurements reveal that our method discovered over 1,400 domains---not present in the original dataset---we suspect to be blocked. In short, automatically updating probe lists is possible, and can help further automate censorship measurements at scale.
SIGMA: Secure GPT Inference with Function Secret Sharing
Authors: Gupta Kanav , Jawalkar Neha , Mukherjee Ananta , Chandran Nishanth , Gupta Divya , Panwar Ashish , Sharma Rahul
Published: July 2024

Secure 2-party computation (2PC) enables secure inference that offers protection for both proprietary machine learning (ML) models and sensitive inputs to them. However, the existing secure inference solutions suffer from high latency and communication overheads, particularly for transformers. Function secret sharing (FSS) is a recent paradigm for obtaining efficient 2PC protocols with a preprocessing phase. We provide Sigma, the first end-to-end system for secure transformer inference based on FSS. By constructing new FSS-based protocols for complex machine learning functionalities, such as Softmax, GeLU and SiLU, and also accelerating their computation on GPUs, Sigma improves the latency of secure inference of transformers by 11 - 19x over the state-of-the-art that uses preprocessing and GPUs. We present the first secure inference of generative pre-trained transformer (GPT) models. In particular, Sigma executes Meta's Llama2 (available on HuggingFace) with 13 billion parameters in 44 seconds and GPT2 in 1.6 seconds
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data
Authors: Guan Vincent , Guépin Florent , Cretu Ana-Maria , de Montjoye Yves-Alexandre
Published: July 2024

Location data is frequently collected from populations and shared in aggregate form to guide policy and decision making. However, the prevalence of aggregated data also raises the privacy concern of membership inference attacks (MIAs). MIAs infer whether an individual's data contributed to the aggregate release. Although effective MIAs have been developed for aggregate location data, these require access to an extensive auxiliary dataset of individual traces over the same locations, which are collected from a similar population. This assumption is often impractical given common privacy practices surrounding location data. To measure the risk of an MIA performed by a realistic adversary, we develop the first Zero Auxiliary Knowledge (ZK) MIA on aggregate location data, which eliminates the need for an auxiliary dataset of real individual traces. Instead, we develop a novel synthetic approach, such that suitable synthetic traces are generated from the released aggregate. We also develop methods to correct for bias and noise, to show that our synthetic-based attack is still applicable when privacy mechanisms are applied prior to release. Using two large-scale location datasets, we demonstrate that our ZK MIA matches the state-of-the-art Knock-Knock (KK) MIA across a wide range of settings, including popular implementations of differential privacy (DP) and suppression of small counts. Furthermore, we show that ZK MIA remains highly effective even when the adversary only knows a small fraction (10%) of their target's location history. This demonstrates that effective MIAs can be performed by realistic adversaries, highlighting the need for strong DP protection.
Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
Authors: Arcolezi Héber H. , Gambs Sébastien
Published: July 2024

While the existing literature on Differential Privacy (DP) auditing predominantly focuses on the centralized model (e.g., in auditing the DP-SGD algorithm), we advocate for extending this approach to audit Local DP (LDP). To achieve this, we introduce the LDP-Auditor framework for empirically estimating the privacy loss of locally differentially private mechanisms. This approach leverages recent advances in designing privacy attacks against LDP frequency estimation protocols. More precisely, through the analysis of numerous state-of-the-art LDP protocols, we extensively explore the factors influencing the privacy audit, such as the impact of different encoding and perturbation functions. Additionally, we investigate the influence of the domain size and the theoretical privacy loss parameters ϵ and δ on local privacy estimation. In-depth case studies are also conducted to explore specific aspects of LDP auditing, including distinguishability attacks on LDP protocols for longitudinal studies and multidimensional data. Finally, we present a notable achievement of our LDP-Auditor framework, which is the discovery of a bug in a state-of-the-art LDP Python package. Overall, our LDP-Auditor framework as well as our study offer valuable insights into the sources of randomness and information loss in LDP protocols. These contributions collectively provide a realistic understanding of the local privacy loss, which can help practitioners in selecting the LDP mechanism and privacy parameters that best align with their specific requirements. We open-sourced LDP-Auditor in [4].
Honesty is the Best Policy: On the Accuracy of Apple Privacy Labels Compared to Apps' Privacy Policies
Authors: Ali Mir Masood , Balash David G. , Kodwani Monica , Kanich Chris , Aviv Adam J.
Published: July 2024

Apple introduced privacy labels in Dec. 2020 as a way for developers to report the privacy behaviors of their apps. While Apple does not validate labels, they also require developers to provide a privacy policy, which offers an important comparison point. In this paper, we fine-tuned BERT-based language models to extract privacy policy features for 474,669 apps on the iOS App Store, comparing the output to the privacy labels. We identify discrepancies between the policies and the labels, particularly as they relate to data collected linked to users. We find that 228K apps' privacy policies may indicate data collection linked to users than what is reported in the privacy labels. More alarming, a large number (97%) of the apps with a Data Not Collected privacy label have a privacy policy indicating otherwise. We provide insights into potential sources for discrepancies, including the use of templates and confusion around Apple's definitions and requirements. These results suggest that significant work is still needed to help developers more accurately label their apps. Our system can be incorporated as a first-order check to inform developers when privacy labels are possibly misapplied.
Raising the Bar: Improved Fingerprinting Attacks and Defenses for Video Streaming Traffic
Authors: Hasselquist David , Witwer Ethan , Carlson August , Johansson Niklas , Carlsson Niklas
Published: July 2024

Despite the clear dominance of video streaming traffic on the Internet and the significant ramifications of disclosure of which videos users are streaming, video fingerprinting has received relatively little attention compared to other traffic analysis domains. Existing attacks are tailored to undefended traffic and mostly rely on a few manually crafted features. Meanwhile, potential defenses are ad hoc, often impractical, and typically only mentioned briefly. Drawing from progress made on website fingerprinting, we aim to improve current standards for attacks and defenses for video streaming traffic while highlighting a critical and underexplored issue on today's Internet. We show that directional and timing-based attacks that leverage CNNs are competitive with state-of-the-art video fingerprinting attacks, in many cases with far less training data. We also provide the first extensive study of potential defenses, which considers performance against attacks, overheads, and user QoE; and we present a novel defense design that boasts both broader applicability and greater efficacy than existing proposals.
Decision-based Data Distribution (D³): Enabling Users to Minimize Data Propagation in Privacy-sensitive Scenarios
Authors: Linsner Sebastian , Demuth Kilian , Fischlin Marc , Reuter Christian
Published: July 2024

In many scenarios, users have to communicate sensitive data with third parties such as doctors, lawyers, insurance companies, social workers, or online shops. Handing over personal data is necessary to use those services, but delegating tasks to increase efficiency still poses the risk that personal data might be leaked. To minimize this risk and further enhance the privacy of users, we propose an interaction concept that uses layered encryption of messages to provide a trade-off between privacy and usability. Users can choose which data is additionally encrypted in an inner layer, e.g. only for the eyes of their doctor, and which data is available in an outer (encrypted or unencrypted) layer for all staff members. Another benefit is the hiding of sensitive data from package inspection or crawling algorithms via emails, while less critical parts can still be processed by these systems via the partial access. To investigate this concept, we derive relevant use cases for form-based communication via email from a quantitative pre-study with 1011 participants, showing that general practitioners are the most suitable use case. We developed demonstrators for this use case and evaluated them in a qualitative study with 42 participants. Our results show that the possibility of minimizing the propagation of sensitive data through additional encryption is highly appreciated and the usage of form-based communication is a promising approach for digital transformation.
Unlinkable Policy-Compliant Signatures for Compliant and Decentralized Anonymous Payments
Authors: Badertscher Christian , Sedaghat Mahdi , Waldner Hendrik
Published: July 2024

Privacy-preserving payment systems face the difficult task of balancing privacy and accountability: on one hand, users should be able to transact privately and anonymously, on the other hand, no illegal activities should be tolerated. The challenging question of finding the right balance lies at the core of the research on accountable privacy that stipulates the use of cryptographic techniques for policy enforcement. Current state-of-the-art systems are only able to enforce rather limited policies, such as spending or transaction limits, or assertions about single participants, but are unable to enforce more complex policies that for example jointly evaluate both, the private credentials of sender and recipient, situations that occur in cross-border payments, let alone to do this without auditors in the loop during payment. This severely limits the cases where decentralized virtual assets can be used in accordance with regulatory compliance such as the Financial Action Task Force (FATF) travel rule, while retaining strong privacy features. We present unlinkable Policy-Compliant Signatures (ul-PCS), an enhanced cryptographic primitive extending the work of Badertscher et al.~(TCC 21). We give rigorous definitions, formally proven constructions, and benchmarks using our prototype developed using CharmCrypto which gives the first insights into feasibility of PCS. Unlinkable PCS has the following unique combination of features: 1) It is an enhanced signature scheme where the public key encodes in a privacy-preserving way the user's verifiable credentials (obtained from a credential authority). 2) Signatures can be created (and later publicly verified) by additionally specifying a recipient's public key aside of the to-be-signed message. A valid signature can only ever be created if the attributes $x_S$ of the signer and the attributes $x_R$ of the receiver fulfill some global policy $F(x_S,x_R)$. 3) The signature can be created by the signer just knowing the recipient's public key; there is no further interaction needed and no information is leaked (beyond the validity of the policy). 4) Once credentials are obtained, a user can generate fresh public keys without interacting with the credential authority. By merging the act of signing a transaction with the act of providing an assurance about the involved participants being compliant with complex policies, yet retain that participants are able to change public keys without the involvement of an authority, we formally show how ul-PCS is a step towards improving regulatory compliance of privacy coins such as Monero or Zcash.
Subgraph Structure Membership Inference Attacks against Graph Neural Networks
Authors: Wang Xiuling , Wang Wendy Hui
Published: July 2024

Graph Neural Networks (GNNs) have been widely applied to various applications across different domains. However, recent studies have shown that GNNs are susceptible to the membership inference attacks (MIAs) which aim to infer if some particular data samples were included in the model’s training data. While most previous MIAs have focused on inferring the membership of individual nodes and edges within the training graph, we introduce a novel form of membership inference attack called the Structure Membership Inference Attack (SMIA) which aims to determine whether a given set of nodes corresponds to a particular target structure, such as a clique or a multi-hop path, within the original training graph. To address this issue, we present novel black-box SMIA attacks that leverage the prediction outputs generated by the target GNN model for inference. Our approach involves training a three-label classifier, which, in combination with shadow training, aids in enabling the inference attack. Our extensive experimental evaluation of three representative GNN models and three real-world graph datasets demonstrates that our proposed attacks consistently outperform three baseline methods, including the one that employs the conventional link membership inference attacks to infer the subgraph structure. Additionally, we design a defense mechanism that introduces perturbations to the node embeddings thus influencing the corresponding prediction outputs by the target model. Our defense selectively perturbs dimensions within the node embeddings that have the least impact on the model's accuracy. Our empirical results demonstrate that the defense effectiveness of our approach is comparable with two established defense techniques that employ differential privacy. Moreover, our method achieves a better trade-off between defense strength and the accuracy of the target model compared to the two existing defense methods.
Onion Services in the Wild: A Study of Deanonymization Attacks
Authors: Tippe Pascal , Tippe Adrian
Published: July 2024

Tor, the leading anonymization network, routes traffic over multiple relays to ensure client anonymity. Its Onion Services allow users to host services within the Tor network without revealing their location. While these techniques are crucial for users in authoritarian regimes and whistleblowers, they are also exploited by criminals. This paper diverges from the common focus on the technical vulnerabilities of the Tor protocol and instead explores the practical aspects of deanonymizing Onion Service users and operators. Despite Tor's robust security mechanisms, human errors in its usage and operation frequently lead to deanonymization. This study models law enforcement agencies as powerful attackers and evaluates documents from 136 court cases to determine investigative methods. We find that investigators employ different methods depending on the offense, with user mistakes being the dominant angle. Technical attacks, though comparatively rare, are highly effective and can potentially impact a large number of users simultaneously. Attacks on the well-researched Tor protocol are exceptionally rare, but their impact is even more significant. We argue that the human aspect of using Tor is the most critical deanonymization angle and that tailored guidelines for ethical users can help protect them from oppressive retaliation while still enabling the prosecution of criminal activity.
Maui: Black-Box Edge Privacy Attack on Graph Neural Networks
Authors: He Haoyu , King Isaiah J. , Huang H. Howie
Published: July 2024

Graphs are ubiquitous data structures with nodes representing objects and edges representing relationships between them. Graph Neural Networks (GNNs) have recently been proposed to study graph-structured data, but unfortunately, are susceptible to privacy leakage. This issue becomes more urgent as GNNs gain wide deployment in many real-world settings including social network analysis, bioinformatics, and cybersecurity. In this paper, we propose the first link inference attack that can compromise user data under the most difficult security settings, which we call Maui. We demonstrate that private edge information can be inferred by a malicious user with a black-box approach. Extensive experiments on six real-world datasets show our attacks conduct effective link inference attacks in various scopes. Our attack achieves significant performance improvements over the current state-of-the-art. When targeting 2-layer Graph Convolution Networks, for inferring edges of a single node, our attack outperforms the best existing method by 12.0%, increasing from 83.7% to 95.7%; when inferring edges of the entire graph, our attack achieves a 19.6% improvement, from 67.7% to 87.3%. Our results underscore the need for countermeasures against privacy attacks in GNNs, as they can reveal rich information about graph structures.
Diversity-driven Privacy Protection Masks Against Unauthorized Face Recognition
Authors: Chow Ka-Ho , Hu Sihao , Huang Tiansheng , Ilhan Fatih , Wei Wenqi , Liu Ling
Published: July 2024

Face recognition (FR) technologies have enabled many life-enriching applications but have also opened doors for potential misuse. Governments, private companies, or even individuals can scrape the web, collect facial images, and build a face database to fuel the FR system to identify human faces without their consent. This paper introduces PMask to combat such a privacy threat against unauthorized FR. It provides a holistic approach to enable privacy-preserving sharing of facial images. PMask preprocesses the facial image and hides its unique facial signature through iterative optimization with dual goals: (i) minimizing the amount of noise to ensure high image quality and (ii) minimizing the perception loss between the privacy-protected face and the original face to ensure the face is recognizable to be the same person by humans. Extensive experiments are conducted on eight representative FR models to evaluate PMask against unauthorized FR. The results validate that PMask provides much stronger protection, introduces less perceptible changes to facial images, and runs faster than state-of-the-art methods to provide privacy protection with a better user experience.
What Do Privacy Advertisements Communicate to Consumers?
Authors: Shen Xiaoxin , Alashwali Eman , Cranor Lorrie
Published: July 2024

When companies release marketing materials aimed at promoting their privacy practices or highlighting specific privacy features, what do they actually communicate to consumers? In this paper, we explore the impact of privacy marketing on: (1) consumers’ attitudes toward the organizations providing the campaigns, (2) overall privacy awareness, and (3) the actionability of suggested privacy advice. To this end, we investigated the impact of four privacy advertising videos and one privacy game published by five different technology companies. We conducted 24 semi-structured interviews with participants randomly assigned to view one or two of the videos or play the game. Our findings suggest that awareness of privacy features can contribute to positive perceptions of a company or its products. The ads we tested were more successful in communicating the advertised privacy features than the game we tested. We observed that advertising a single privacy feature using a single metaphor in a short ad increased awareness of the advertised feature. The game failed to communicate privacy features or motivate study participants to use the features. Our results also suggest that privacy campaigns can be useful for raising awareness about privacy features and improving brand image, but may not be the most effective way to teach viewers how to use privacy features.
Provable Security Analysis of Butterfly Key Mechanism Protocol in IEEE 1609.2.1 Standard
Authors: Boldyreva Alexandra , Kumar Virendra , Sun Jiahao
Published: July 2024

The paper provides the first provable security analysis of the Butterfly Key Mechanism (BKM) protocol from IEEE 1609.2.1 standard. The BKM protocol specifies a novel approach for efficiently requesting multiple certificates for use in vehicle-to-everything (V2X) communication. We define the main security goals of BKM, such as vehicle privacy and communication authenticity. We prove that the BKM protocol, with small modifications, meets those security goals. We also propose a way to significantly improve the protocol's efficiency without sacrificing security.
Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API
Authors: Aksu Hidayet , Ghazi Badih , Kamath Pritish , Kumar Ravi , Manurangsi Pasin , Sealfon Adam , Varadarajan Avinash V.
Published: July 2024

The Privacy Sandbox Attribution Reporting API has been recently deployed by Google Chrome to support the basic advertising functionality of attribution reporting (aka conversion measurement) after deprecation of third-party cookies. The API implements a collection of privacy-enhancing guardrails including contribution bounding and noise injection. It also offers flexibility for the analyst to allocate the contribution budget. In this work, we present algorithms for optimizing the allocation of the contribution budget for summary reports from the Attribution Reporting API. We develop a synthetic data model that we find to accurately capture real-world conversion data, and extensively evaluate our method on two real-world datasets and two synthetic datasets. We show that optimizing the parameters that can be set by the analyst can significantly improve the utility achieved by querying the API while satisfying the same privacy bounds.
Deniability in Automated Contact Tracing: Impossibilities and Possibilities
Authors: Günther Christoph U. , Pietrzak Krzysztof
Published: July 2024

Automated contact tracing (ACT) emerged as a promising measure to curb the spread of Covid-19. Users enable ACT on their smartphones to automatically record contacts with other users. If a user tests positive for the disease, they report their diagnosis to alert their contacts.
Designing effective ACT protocols is challenging since they need to be efficient and secure while also ensuring users' privacy. As ACT protocols necessarily leak some information by design, defining privacy is difficult. For example, a user cannot deny having met another user. Ideally, however, the user can plausibly deny everything else, in particular, when they met. We call this privacy property contact-time deniability.
While some early works discussed contact-time deniability informally, it has received little attention since then. We investigate deniability from a rigorous, theoretical point of view and arrive at the following impossibility result:
A decentralized protocol with unidirectional communication cannot be contact-time deniable and replay-secure. This holds even if malicious users treat smartphones as black-boxes.
Unidirectional protocols are usually very efficient and many proposals are unidirectional, e.g., the widely-deployed Google-Apple Exposure Notifications. So the impossibility result considerably constrains the design space of efficient, secure, and private ACT protocols. However, it can also be used as a guide; we discuss several possibilities to achieve contact-time deniability in practice.
Scalable Metadata-Hiding for Privacy-Preserving IoT Systems
Authors: Chen Yunang , Heath David , Chatterjee Rahul , Fernandes Earlence
Published: July 2024

Modern cloud-based IoT services comprise an integrator service and several device vendor services. The vendor services enable users to remotely control their devices, while the integrator serves as a central intermediary, offering a unified interface for managing devices from different vendors. Although such a model is quite beneficial for IoT services to evolve quickly, it also creates a serious privacy concern: the vendor and integrator services observe all interactions between users and devices. Toward this, we propose Mohito, a privacy-preserving IoT system that hides such interactions from both the integrator and the vendors. In Mohito, we protect both the interaction data and the metadata, so that no one learns which user is communicating with which device. By utilizing oblivious key-value storage as a primitive and leveraging the unique communication graph of IoT services, we build a scalable protocol specialized in handling large concurrent traffic, a common demand in IoT systems. Our evaluation shows that Mohito can achieve up to 600x more throughput than the state-of-the-art general-purpose systems that provide similar security guarantees.
Our Data, Our Solutions: A Participatory Approach for Enhancing Privacy in Wearable Activity Tracker Third-Party Apps
Authors: Zufferey Noé , Salehzadeh Niksirat Kavous , Humbert Mathias , Huguenin Kévin
Published: July 2024

Wearable activity trackers (WATs) have recently gained worldwide popularity, with over a billion devices collecting a range of personal data. To receive additional services, users commonly share this data with third-party applications (TPAs). However, this practice poses potential privacy risks. Privacy-enhancing technologies have been developed to address these concerns, but they often lack user-centered design, and therefore, are less likely to be directly related to users' concerns and to be widely adopted. This study takes a participatory design approach involving N=26 experienced WAT users who share data with TPAs. Through a series of design sessions, participants conceptualized 19 solutions, from which we identified seven different design features. We further analyze and discuss how these features can be combined to assist users in managing their data sharing with TPAs and, therefore, enhancing their privacy. Finally, we selected the three most promising features, namely partial sharing, reminder, and revocation assistance, and conducted an online survey with N=201 WAT users to better understand the potential effectiveness and usability of these features. This work makes an important contribution by offering user-centered solutions and valuable insights for integrating privacy-enhancing technologies into the WAT ecosystem.